| 2018 | Yuanzhi Li, Yingyu Liang | Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data |
| 2019 | Greg Ongie, Rebecca Willett, Daniel Soudry, and Nathan Srebro | A function space view of bounded norm infinite width relu nets: The multivariate case |
| 2019 | Z. Charles, H. Rosenberg, D. Papailiopoulos | A Geometric Perspective on the Transferability of Adversarial Directions |
| 2019 | Sylvain Arlot, Alain Celisse, Zaid Harchaoui | A Kernel Multiple Change-point Algorithm via Model Selection |
| 2019 | Alexander Greaves-Tunnell, Zaid Harchaoui | A Statistical Investigation of Long Memory in Language and Music |
| 2019 | Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, and Cho-Jui Hsieh | A unified framework for data poisoning attack to graph-based semi-supervised learning |
| 2019 | Vincent Roulet, Zaid Harchaoui | An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks |
| 2019 | Hongzhou Lin, Julien Mairal, Zaid Harchaoui | An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration |
| 2019 | Xie, Y. and Wright, S. J. | Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints |
| 2019 | Z Charles, S Rajput, S Wright, D Papailiopoulos | Convergence and Margin of Adversarial Training on Separable Data |
| 2019 | Yuzhe Ma, Xiaojin Zhu, and Justin Hsu | Data Poisoning against Differentially-Private Learners: Attacks and Defenses |
| 2019 | S Rajput, H Wang, Z Charles, D Papailiopoulos | DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation |
| 2019 | Kit Newton, Qin Li and Andrew Stuart | Diffusive optical tomography in the Bayesian framework |
| 2019 | S Rajput, Z. Feng, Z. Charles, P.-L. Loh, D. Papailiopoulos | Does Data Augmentation Lead to Positive Margin? |
| 2019 | Glendening, E., Wright, S. J., and Weinhold, F. | Efficient optimization of natural resonance theory weightings and bond orders by Gram-based convex programming |
| 2019 | Owen Levin, Zihang Meng, Vikas Singh, Xiaojin Zhu | Fooling Computer Vision into Inferring the Wrong Body Mass Index |
| 2019 | Farida Enikeeva, Zaid Harchaoui | High-dimensional Change-point Detection under Sparse Alternatives |
| 2019 | Vincent Roulet, Siddhartha Srinivasa, Dmitriy Drusvyatskiy, Zaid Harchaoui | Iterative Linearized Control: Stable Algorithms and Complexity Guarantees |
| 2019 | Zeyuan Allen-Zhu, Yuanzhi Li, Yingyu Liang | Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers |
| 2019 | Zhu, Z., Li, X., Wang, M., and Zhang, A. | Learning Markov models via low-rank optimization |
| 2019 | Shengchao Liu, Mehmet Furkan Demirel, Yingyu Liang | N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules |
| 2019 | D. Gilton, G. Ongie, and R. Willett | Neumann networks for inverse problems in imaging |
| 2019 | Xuezhou Zhang, Xiaojin Zhu, and Laurent Lessard | Online Data Poisoning Attacks |
| 2019 | Yiding Chen and Xiaojin Zhu | Optimal Adversarial Attack on Autoregressive Models |
| 2019 | Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu | Policy Poisoning in Batch Reinforcement Learning and Control |
| 2019 | Zhang H, Ericksen SS, Lee C-p, Ananiev GE, Wlodarchak N, Yu P, Mitchell JC, Gitter A, Wright SJ, Hoffman FM, Wildman SA, Newton MA | Predicting kinase inhibitors using bioactivity matrix derived informer sets |
| 2019 | Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, and Adish Singla | Preference-based batch and sequential teaching: Towards a unified view of models |
| 2019 | Hongyang Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang | Recovery Guarantees for Quadratic Tensors with Limited Observations |
| 2019 | R. M. Willett | Response to Òartificial intelligenceÑthe revolution hasnÕt happened yet" |
| 2019 | Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha | Robust Attribution Regularization |
| 2019 | Ke Chen, Qin Li, Stephen J. Wright | Schwarz iteration method for elliptic equation with rough media based on random sampling |
| 2019 | Ayon Sen, Xiaojin Zhu, Liam Marshall, Robert Nowak | Should Adversarial Attacks Use Pixel p-Norm? |
| 2019 | Sanjoy Dasgupta, Daniel Hsu, Stefanos Poulis, Xiaojin Zhu | Teaching a black-box learner |
| 2020 | Haotian Jiang, Tarun Kathuria, Yin Tat Lee, Swati Padmanabhan, Zhao Song | A Faster Interior Point Method for Semidefinite Programming |
| 2020 | Luo, Y., Han, R. and Zhang, A. R. | A Schatten-q matrix perturbation theory via perturbation projection error bound |
| 2020 | Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian | Acceleration with a Ball Optimization Oracle |
| 2020 | Haotian Jiang, Yin Tat Lee, Zhao Song, Sam Chiu-wai Wong | An improved cutting plane method for convex optimization, convex-concave games, and its applications |
| 2020 | Yin Tat Lee, Swati Padmanabhan | An Í(m/_3.5)-Cost Algorithm for Semidefinite Programs with Diagonal Constraints |
| 2020 | Rungang Han, Rebecca Willett, and Anru Zhang | An optimal statistical and computational framework for generalized tensor estimation |
| 2020 | Wright, S. J. and Lee, C.-p. | Analyzing random permutations for cyclic coordinate descent |
| 2020 | Yuling Yan, Bret Hanlon, Sebastien Roch and Karl Rohe | Asymptotic seed bias in respondent-driven sampling |
| 2020 | Zaid Harchaoui, Lang Liu, Soumik Pal | Asymptotics of Entropy-Regularized Optimal Transport via Chaos Decomposition |
| 2020 | H. Wang, K. Sreenivasan, S. Rajput, H. Vishwakarma, S. Agarwal, J.Y, Sohn, K. Lee, and D. Papailiopoulos | Attack Of The Tails: Yes, You Really Can Backdoor Federated Learning |
| 2020 | S. Liu, D. Papailiopoulos, D. Achlioptas | Bad Global Minima Exist and SGD Can Reach Them |
| 2020 | Jan van den Brand, Yin Tat Lee, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang | Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs |
| 2020 | SŽbastien Bubeck, Bo'az Klartag, Yin Tat Lee, Yuanzhi Li, Mark Sellke | Chasing Nested Convex Bodies Nearly Optimally |
| 2020 | Shashank Rajput, Anant Gupta, Dimitris Papailiopoulos | Closing the convergence gap of SGD without replacement |
| 2020 | Sally Dong, Yin Tat Lee, Kent Quanrud | Computing Circle Packing Representations of Planar Graphs |
| 2020 | Mardia, Jay, Jiantao Jiao, Ervin T‡nczos, Robert D. Nowak, and Tsachy Weissman | Concentration inequalities for the empirical distribution of discrete distributions: beyond the method of types |
| 2020 | L. Zheng, R. Willett, and G. Raskutti | Context-dependent self-exciting point processes:models, methods, and risk bounds in high dimensions |
| 2020 | G. Ongie, C. Metzler, A. Jalal, A. Dimakis, R. Baraniuk, and R. Willett | Deep learning techniques for inverse problems in imaging |
| 2020 | Zhang, C., Han, R., Zhang, A. R., and Voyles, P. M. | Denoising Atomic Resolution 4D Scanning Transmission Electron Microscopy Data with Tensor Singular Value Decomposition |
| 2020 | D. Wang, Y. Yu, and R. Willett | Detecting abrupt changes in high-dimensional self-exciting poisson processes |
| 2020 | D. Gilton, R. Luo, R. Willett, and G. Shakhnarovich | Detection and description of change in visual streams |
| 2020 | Marek Eli‡s, Michael Kapralov, Janardhan Kulkarni, Yin Tat Lee | Differentially Private Release of Synthetic Graphs |
| 2020 | Corinne Jones, Zaid Harchaoui | End-to-End Learning for Retrospective Change-Point Estimation |
| 2020 | Zhiyan Ding, Lukas Einkemme and Qin Li | Dynamical Low-Rank Integrator for the Linear Boltzmann Equation: Error Analysis in the Diffusion Limit |
| 2020 | Han, R., Luo, Y., Wang, M., and Zhang, A. R. | Exact Clustering in Tensor Block Model: Statistical Optimality and Computational Limit |
| 2020 | H Wang, M Yurochkin, Y Sun, D Papailiopoulos, Y Khazaeni | Federated Learning with Matched Averaging |
| 2020 | Yassine Laguel, Jerome Malick, Zaid Harchaoui | First-order Optimization for Superquantile-based Supervised Learning |
| 2020 | D. Wang, Z. Zhao, R. Willett, and C. Y. Yau | Functional autoregressive processes in reproducing kernel hilbert spaces |
| 2020 | D. Wang, Z. Zhao, Y. Yu, and R. Willett | Functional linear regression with mixed predictors |
| 2020 | Mukherjee, S., Tripathy, A. and Nowak, R | Generalized Chernoff Sampling for Active Learning and Structured Bandit Algorithms |
| 2020 | Fangzhou Mu, Yin Li, Yingyu Liang | Gradients as Features for Deep Representation Learning |
| 2020 | Y. Li, B. Mark, G. Raskutti, R.Willett, H. Song, and D. Neiman | Graph-based regularization for regression problems with alignment and highly-correlated designs |
| 2020 | Meyer Scetbon, Zaid Harchaoui | Harmonic Decompositions of Convolutional Networks |
| 2020 | Wai-Tong Louis Fan, Brandon Legried & Sebastien Roch | Impossibility of Consistent Distance Estimation from Sequence Lengths Under the TKF91 Model. |
| 2020 | Wai-Tong Louis Fan, Brandon Legried and Sebastien Roch | Impossibility of phylogeny reconstruction from k-mer counts |
| 2020 | Lee, C.-p. and Wright, S. J. | Inexact variable metric stochastic block-coordinate descent for regularized optimization |
| 2020 | Xia, D., Zhang, A. R., and Zhou, Y. | Inference for low-rank tensorsÐno need to debias |
| 2020 | Anru Zhang, Yuetian Luo, Garvesh Raskutti, and Ming Yuan | ISLET: Fast and optimal low-rank tensor regression via importance sketching |
| 2020 | Hui Yuan, Yingyu Liang | Learning Entangled Single-Sample Distributions via Iterative Trimming |
| 2020 | Miaoyan Wang and Lexin Li | Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and Its Statistical Optimality |
| 2020 | Naman Agarwal, Sham M. Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford | Leverage Score Sampling for Faster Accelerated Regression and ERM |
| 2020 | W. J. Marais, R. E. Holz, J. S. Reid, and R. M. Willett | Leveraging spatial textures, through machine learning, to identify aerosol and distinct cloud types from multispectral observations |
| 2020 | D. Wang, Y. Yu, A. Rinaldo, and R. Willett | Localizing changes in high-dimensional vector autoregressive processes |
| 2020 | Yin Tat Lee, Ruoqi Shen, Kevin Tian | Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo |
| 2020 | Chen, S., Li, Q., Lu, J., and Wright, S. J. | Manifold learning and nonlinear homogenization |
| 2020 | Karzand, Mina, and Robert D. Nowak | MaxiMin Active Learning in Overparameterized Model Classes |
| 2020 | SŽbastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer | Network size and size of the weights in memorization with two-layers neural networks |
| 2020 | Vincent Roulet, Maryam Fazel, Siddhartha Srinivasa, Zaid Harchaoui | On the Convergence of the ILEQG Algorithm to Stationary Points |
| 2020 | Cai, T. T., Han, R., and Zhang, A. R. | On the non-asymptotic concentration of heteroskedastic Wishart-type random matrix |
| 2020 | Luo, Y. and Zhang, A. R. | Open Problem: Average-Case Hardness of Hypergraphic Planted Clique Detection. |
| 2020 | Yiding Chen and Xiaojin Zhu | Optimal attack against autoregressive models by manipulating the environment |
| 2020 | Malloy, M.L., Tripathy, A. and Nowak, R.D | Optimal confidence regions for the multinomial parameter |
| 2020 | A. Pensia, S. Rajput, A. Nagle, H. Vishwakarma, D. Papailiopoulos | Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient |
| 2020 | Zhou, Y., Zhang, A. R., Zheng, L., and Wang, Y. | Optimal Ultrahigh-order tensor SVD via tensor-train orthogonal iteration |
| 2020 | Ru-Yu Lai and Qin Li | Parameter Reconstruction for general transport equation |
| 2020 | Niao He, Zaid Harchaoui, Yichen Wang, Le Song | Point Process Estimation with Mirror Prox Algorithms |
| 2020 | Brandon Legried, Erin Molloy, Tandy Warnow, and Sebastien Roch | Polynomial-Time Statistical Estimation of Species Trees Under Gene Duplication and Loss |
| 2020 | Sen, Ayon, Xiaojin Zhu, Erin Marshall, and Robert Nowak | Popular Imperceptibility Measures in Visual Adversarial Attacks are Far from Human Perception |
| 2020 | Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian | Positive semidefinite programming: mixed, parallel, and width-independent |
| 2020 | B. D. Luck, J. L. Drewry, R. D. Shaver, R. M. Willett, and L. F. Ferraretto | Predicting in situ dry matter degradability of chopped and processed corn kernels using image analysis techniques |
| 2020 | Ng, T. L. and Newton, M. A. | Random weighting to approximate posterior inference in LASSO regression |
| 2020 | GŸrbŸzbalaban, M., Ozdaglar, A., Vanli, N. D., and Wright, S. J. | Randomness and permutations in coordinate descent methods |
| 2020 | Luo, Y., Huang, W., Li, X., and Zhang, A. R. | Recursive importance sketching for rank constrained least squares: Algorithms and high-order convergence |
| 2020 | Wang, Jinyi, and Vivak Patel | Reduced-Memory Kalman Based Stochastic Gradient Descent |
| 2020 | Yilin Zhang, Karl Rohe, Sebastien Roch | Reducing Seed Bias in Respondent-Driven Sampling by Estimating Block Transition Probabilities |
| 2020 | Krishna Pillutla, Sham M. Kakade Zaid Harchaoui | Robust Aggregation for Federated Learning |
| 2020 | Johnston, Liam, and Vivak Patel | Second-Order Sensitivity Methods for Robustly Training Recurrent Neural Network Models |
| 2020 | Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang | Sketching Transformed Matrices with Applications to Natural Language Processing |
| 2020 | Jan van den Brand, Yin Tat Lee, Aaron Sidford, Zhao Song | Solving tall dense linear programs in nearly linear time |
| 2020 | Cai, T. T., Zhang, A., and Zhou, Y. | Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference |
| 2020 | Max Hill, Brandon Legried and Sebastien Roch | Species tree estimation under joint modeling of coalescence and duplication: sample complexity of quartet methods |
| 2020 | Louis Fan and Sebastien Roch | Statistically consistent and computationally efficient inference of ancestral DNA sequences in the TKF91 model under dense taxon sampling |
| 2020 | Aditi Laddha, Yin Tat Lee, Santosh S. Vempala | Strong self-concordance and sampling |
| 2020 | Ke Chen, Qin Li, Kit Newton, Steve Wright | Structured random sketching for PDE inverse problems |
| 2020 | Luo, Y. and Zhang, A. R. | Tensor clustering with planted structures: Statistical optimality and computational limits |
| 2020 | Chanwoo Lee and Miaoyan Wang | Tensor denoising and completion based on ordinal observations |
| 2020 | Parhi, Rahul, and Robert D. Nowak | The role of neural network activation functions |
| 2020 | Julian Katz-Samuels, Lalit Jain, Zohar Karnin, Kevin Jamieson | An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits |
| 2020 | Blake Mason, Lalit Jain, Ardhendu Tripathy, Robert Nowak | Finding All {\epsilon}-Good Arms in Stochastic Bandits |
| 2020 | Yinglun Zhu, Sumeet Katariya, and Robert Nowak | Robust Outlier Arm Identification |
| 2020 | Yinglun Zhu, and Robert Nowak | On Regret with Multiple Best Arms |
| 2021 | Minyi Dai, Mehmet F. Demirel, Yingyu Liang, Jia-Mian Hu | Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials |
| 2021 | C. Jones, S. Clayton, F. Ribalet, E. V. Armbrust, Z. Harchaoui | A Kernel-Based Change Detection Method to Map Shifts in Phytoplankton Communities Measured by Flow Cytometry |
| 2021 | O'Neill, M. and Wright, S. J. | A log-barrier Newton-CG method for bound constrained optimization with complexity guarantees |
| 2021 | Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright | A low-rank Schwarz method for radiative transfer equation with heterogeneous scattering coefficient |
| 2021 | Luo, Y., Raskutti, G., Yuan, M., and Zhang, A. R. | A sharp blockwise tensor perturbation bound for orthogonal iteration |
| 2021 | Meyer Scetbon, Zaid Harchaoui | A Spectral Analysis of Dot-product Kernels |
| 2021 | Yassine Laguel, Krishna Pillutla, JŽr™me Malick, Zaid Harchaoui | A Superquantile Approach to Federated Learning with Heterogeneous Devices |
| 2021 | D. Davis, D. Drusvyatskiy | Active strict saddles in nonsmooth optimization |
| 2021 | Vivak Patel, Mohammad Jahangoshahi, and Daniel Adrian Maldonado | An Implicit Representation and Iterative Solution of Randomly Sketched Linear Systems |
| 2021 | Chanwoo Lee, Miaoyan Wang | Beyond the Signs: Nonparametric Tensor Completion via Sign Series |
| 2021 | Vivak Patel, Mohammad Jahangoshahi, and Daniel Adrian Maldonado | Convergence of Adaptive, Randomized, Iterative Linear Solvers |
| 2021 | Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh | FairBatch: Batch Selection for Model Fairness |
| 2021 | Samuel Ainsworth, Kendall Lowrey, John Thickstun, Zaid Harchaoui, Siddhartha Srinivasa | Faster Policy Learning with Continuous-Time Gradients |
| 2021 | D. Davis, D. Drusvyatskiy, L. Xiao, J. Zhang | From low probability to high confidence in stochastic optimization |
| 2021 | A. Stevens, R. Willett, A. Mamalakis, E. Foufoula-Georgiou, A. Tejedor, J. T. Randerson, P. Smyth, and S. Wright | Graph-guided regularized regression of pacific ocean climate variables to increase predictive skill of southwestern US winter precipitation |
| 2021 | Romain Camilleri, Julian Katz-Samuels, Kevin Jamieson | High-Dimensional Experimental Design and Kernel Bandits |
| 2021 | Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson | Improved Algorithms for Agnostic Pool-based Active Classification |
| 2021 | Yifang Chen, Simon S. Du, Kevin Jamieson | Improved Corruption Robust Algorithms for Episodic Reinforcement Learning |
| 2021 | Kumar, P., Rawlings, J.B., and Wright, S.J. | Industrial, large-scale model predictive control with structured neural networks |
| 2021 | Ethan K. Gordon, Sumegh Roychowdhury, Tapomayukh Bhattacharjee, Kevin Jamieson, Siddhartha S. Srinivasa | Leveraging Post Hoc Context for Faster Learning in Bandit Settings with Applications in Robot-Assisted Feeding |
| 2021 | V. Charisopoulos, Y. Chen, D. Davis, M. Diaz, L. Ding, D. Drusvyatskiy | Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence |
| 2021 | Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaid Harchaoui | MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation |
| 2021 | D. Gilton, G. Ongie, and R. Willett | Model adaptation for inverse problems in imaging |
| 2021 | Chanwoo Lee, Lexin Li, Hao Helen Zhang, and Miaoyan Wang | Nonparametric Trace Regression in High Dimensions via Sign Series Representation |
| 2021 | Ding, Z., Li, Q., Lu, J., and Wright, S.J. | Random coordinate Langevin Monte Carlo |
| 2021 | Ding, Z., Li, Q., Lu, J., and Wright, S. J. | Random coordinate underdamped Langevin Monte Carlo |
| 2021 | Chen, K., Li, Q., Lu, J., and Wright, S.J. | Random sampling and efficient algorithms for multiscale PDEs |
| 2021 | Ke Chen, Qin Li, Jianfeng Lu, Steve Wright | Randomized sampling for basis functions construction in generalized finite element methods |
| 2021 | Lang Liu, Joseph Salmon, Zaid Harchaoui | Score-based Change Detection for Gradient-based Learning Machines |
| 2021 | Daren Wang, Kevin Lin, and Rebecca Willett | Statistically and computationally efficient change point localization in regression settings |
| 2021 | Patel, Vivak and Shushu Zhang | Stochastic Gradient Descent on Nonconvex Functions with General Noise Models |
| 2021 | D.Drusvyatskiy, L. Xiao | Stochastic optimization with decision-dependent distributions |
| 2021 | Jiaxin Hu, Chanwoo Lee, and Miaoyan Wang | Generalized Tensor Decomposition with features on multiple modes |
| 2021 | Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson | Task-Optimal Exploration in Linear Dynamical Systems |
| 2021 | G. Ongie, D. Pimentel-Alarcon, L. Balzano, R. Nowak, and R. Willett | Tensor methods for nonlinear matrix completion |
| 2021 | Curtis, F. E., Robinson, D. P., Royer, C. W., and Wright, S. J. | Trust-region Newton-CG with strong second- order complexity guarantees for nonconvex optimization |
| 2021 | Bšhm, A. and Wright, S.J. | Variable smoothing for weakly convex composite functions |
| 2021 | Song, C., Wright, S.J. and Diakonikolas, J. | Variance reduction via prima-dual accelerated dual averaging for nonsmooth convex finite sums |
| 2021 | Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson | Experimental Design for Regret Minimization in Linear Bandits |
| 2021 | Jifan Zhang, Kevin Jamieson | Learning to Actively Learn: A Robust Approach |
| 2021 | Davis Gilton, Gregory Ongie, Rebecca Willett | Deep Equilibrium Architectures for Inverse Problems in Imaging |
| 2021 | Hyebin Song, Garvesh Raskutti, Rebecca Willett | Prediction in the presence of response-dependent missing labels |
| 2021 | Takuya Kurihana, Elisabeth Moyer, Rebecca Willett, Davis Gilton, Ian Foster | Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder |
| 2021 | Changhun Jo, Kangwook Lee | Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information |
| 2021 | Blake Mason, Ardhendu Tripathy, Robert Nowak | Nearest Neighbor Search Under Uncertainty |
| 2021 | Kwang-sung Jun, Lalit Jain, Blake Mason, Housam Nassif | Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits |
| 2021 | Chanwoo Lee, Miaoyan Wang | Smooth tensor estimation with unknown permutations |
| 2021 | Jasper C.H. Lee, Paul Valiant | Optimal Sub-Gaussian Mean Estimation in R |
| 2021 | Nan Chen and Yingda Li | BAMCAFE: A Bayesian machine learning advanced forecast ensemble method for complex turbulent systems with partial observations |
| 2021 | Suman K. Bera and Noujan Pashanasangi and C. Seshadhri | Near-Linear Time Homomorphism Counting in Bounded Degeneracy Graphs: The Barrier of Long Induced Cycles |
| 2021 | Noujan Pashanasangi and C. Seshadhri | Faster and Generalized Temporal Triangle Counting, via Degeneracy Ordering |
| 2021 | Akash Kumar and C. Seshadhri and Andrew Stolman | Random walks and forbidden minors III: $\text{poly}\left(d\varepsilon ^{-1}\right)$-time partition oracles for minor-free graph classes |
| 2021 | L. Einkemmer, Z. Ding and Qin Li | Dynamical Low-Rank Integrator for the Linear Boltzmann Equation: Error Analysis in the Diffusion Limit |
| 2021 | Z. Ding and Qin Li | Langevin Monte Carlo: random coordinate descent and variance reduction |
| 2021 | Reilly Raab and Yang Liu | Unintended Selection: Persistent Qualification Rate Disparities and Interventions |
| 2021 | Yang Liu and Jialu Wang | Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial |
| 2021 | Jialu Wang, Yang Liu, Xin Eric Wang | Are Gender-Neutral Queries Really Gender-Neutral?
Mitigating Gender Bias in Image Search |
| 2021 | Sally Dong, Yin Tat Lee, Guanghao Ye | A nearly-linear time algorithm for linear programs with small treewidth: a multiscale representation of robust central path. |
| 2021 | He Jia, Aditi Laddha, Yin Tat Lee, Santosh S. Vempala | Reducing isotropy and volume to KLS: an o*(n3_2) volume algorithm. |
| 2021 | Jan van den Brand, Yin Tat Lee, Yang P. Liu, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang | Minimum cost flows, MDPs, and _1-regression in nearly linear time for dense instances. |
| 2021 | Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat | Fast and Memory Efficient Differentially Private-SGD via JL Projections |
| 2021 | Yin Tat Lee, Ruoqi Shen, Kevin Tian | Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. |
| 2021 | Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz | Numerical Composition of Differential Privacy. |
| 2021 | Janardhan Kulkarni, Yin Tat Lee, Daogao Liu | Private Non-smooth ERM and SCO in Subquadratic Steps. |
| 2021 | Yin Tat Lee, Ruoqi Shen, Kevin Tian | Structured Logconcave Sampling with a Restricted Gaussian Oracle. |
| 2021 | Julian Katz-Samuels, Blake Mason, Kevin Jamieson, Rob Nowak | Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers |
| 2021 | Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui | Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals |
| 2021 | Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaid Harchaoui | MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers |
| 2021 | Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui | Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees |
| 2021 | Lang Liu, Soumik Pal, Zaid Harchaoui | Entropy Regularized Optimal Transport Independence Criterion |
| 2021 | Fan Chen, Sebastien Roch, Karl Rohe, and Shuqi Yu | Estimating graph dimension with cross-validated eigenvalues |
| 2021 | Varun Embar, Sriram Srinivasan, and Lise Getoor | A Comparison of Statistical Relational Learning and Graph Neural Networks for Aggregate Graph Queries |
| 2021 | Sriram Srinivasan, Charles Dickens, Eriq Augustine, Golnoosh Farnadi, and Lise Getoor | A Taxonomy of Weight Learning Methods for Statistical Relational Learning |
| 2021 | arun Embar, Andrey Kan, Bunyamin Sisman, Christos Faloutsos, and Lise Getoor | DiffXtract: Joint Discriminative Product Attribute-Value Extraction |
| 2021 | Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, and Robert Nowak | Pure Exploration in Kernel and Neural Bandits |
| 2021 | Parhi, Rahul, and Robert D. Nowak | Banach Space Representer Theorems for Neural Networks and Ridge Splines |
| 2021 | Ran Dai, Hyebin Song, Rina Foygel Barber, Garvesh Raskutti | Convergence guarantee for the sparse monotone single index model |
| 2021 | Byol Kim and Rina Foygel Barber | Black box tests for algorithmic stability |
| 2021 | Yonghoon Lee and Rina Foygel Barber | Distribution-free inference for regression: discrete, continuous, and in between |
| 2021 | Yonghoon Lee and Rina Foygel Barber | Binary classification with corrupted labels |
| 2021 | Julia Lindberg, Carlos AmŽndola, Jose Israel Rodriguez | Estimating Gaussian mixtures using sparse polynomial moment systems |
| 2021 | Julia Lindberg, Nathan Nicholson, Jose Israel Rodriguez, Zinan Wang | Maximum likelihood degrees of sparse polynomial systems |
| 2021 | Laurentiu G. Maxim, Jose Israel Rodriguez, Botong Wang | Euclidean distance degree of projective varieties |
| 2021 | Yue Sun, Adhyyan Narang, Ibrahim Gulluk, Samet Oymak, Maryam Fazel | Towards sample-efficient overparameterized meta-learning |
| 2021 | Yue Sun, Maryam Fazel | Learning optimal controllers by policy gradient: Global optimality via convex parameterization |
| 2022 | Ho-Nguyen, N. and Wright, S. J. | Adversarial classification via distributional robustness with Wasserstein ambiguity |
| 2022 | Gautam Dasarathy, Elchanan Mossel, Robert Nowak and Sebastien Roch | A stochastic Farris transform for genetic data under the multispecies coalescent with applications to data requirements |
| 2022 | Nan Chen,Yingda Li and Honghu Liu | Conditional Gaussian nonlinear system: A fast preconditioner and a cheap surrogate model for complex nonlinear systems |
| 2022 | Jeffrey Covington, Nan Chen, and Monica M Wilhelmus | Bridging Gaps in the Climate Observation Network: A Physics-based Nonlinear Dynamical Interpolation of Lagrangian Ice Floe Measurements via Data-Driven Stochastic Models |
| 2022 | Sabyasachi Basu and Akash Kumar and C. Seshadhri | The complexity of testing all properties of planar graphs, and the role of isomorphism |
| 2022 | Balaram Behera and Edin Husic and Shweta Jain and Tim Roughgarden and C. Seshadhri | {FPT} Algorithms for Finding Near-Cliques in c-Closed Graphs |
| 2022 | Andrew Stolman, Caleb Levy, C. Seshadhri, and Aneesh Sharma | Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling |
| 2022 | Z. DIng, S. Chen, Qin Li, and S.J. Wright | Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis |
| 2022 | Ahmet Alacaoglu, Volkan Cevher, Stephen J Wright | On the Complexity of a Practical Primal-Dual Coordinate Method |
| 2022 | K Chen, S Chen, Qin Li, J Lu, SJ Wright | Low-rank approximation for multiscale PDEs |
| 2022 | C Song, CY Lin, SJ Wright, J Diakonikolas | Coordinate Linear Variance Reduction for Generalized Linear Programming |
| 2022 | Z Yao, P Xu, F Roosta, SJ Wright, MW Mahoney | Inexact Newton-CG Algorithms With Complexity Guarantees |
| 2022 | Subhojyoti Mukherjee, Ardhendu Tripathy, Robert Nowak | Chernoff Sampling for Active Testing and Extension to Active Regression |
| 2022 | Blake Mason, Romain Camilleri, Subhojyoti Mukherjee, Kevin Jamieson, Robert Nowak, Lalit Jain | Nearly Optimal Algorithms for Level Set Estimation |
| 2022 | Subhojyoti Mukherjee | Safety Aware Changepoint Detection for Piecewise iid Bandits |
| 2022 | Subhojyoti Mukherjee, Josiah P Hanna, Robert Nowak | ReVar: Strengthening Policy Evaluation via Reduced Variance Sampling |
| 2022 | T. Bui, Qin Li and L. Zepeda-Nunez | Bridging and Improving Theoretical and Computational Electrical Impedance Tomography via Data Completion |
| 2022 | Jasper C.H. Lee, Paul Valiant | Optimal Sub-Gaussian Mean Estimation in Very High Dimensions |
| 2022 | Shivam Gupta, Jasper C.H. Lee, Eric Price, Paul Valiant | Finite-Sample Maximum Likelihood Estimation of Location |
| 2022 | Jialu Wang, Yang Liu, Xin Eric Wang | Assessing Multilingual Fairness in Pre-trained Multimodal Representations |
| 2022 | Jan van den Brand, Yu Gao, Arun Jambulapati, Yin Tat Lee, Yang P. Liu, Richard Peng, Aaron Sidford | Faster maxflow via improved dynamic spectral vertex sparsifiers. |
| 2022 | Maryam Fazel, Yin Tat Lee, Swati Padmanabhan, Aaron Sidford | Computing Lewis Weights to High Precision. |
| 2022 | Sally Dong, Yu Gao, Gramoz Goranci, Yin Tat Lee, Richard Peng, Sushant Sachdeva, Guanghao Ye | Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time. |
| 2022 | Julian Katz-Samuels, Julia Nakhleh, Robert Nowak, Yixuan Li | Training OOD Detectors in their Natural Habitats |
| 2022 | Jifan Zhang, Julian Katz-Samuels, Robert Nowak | GALAXY: Graph-based Active Learning at the Extreme |
| 2022 | Yinglun Zhu, Julian Katz-Samuels, Robert Nowak | Near Instance Optimal Model Selection for Pure Exploration Linear Bandits |
| 2022 | Cody Coleman, Edward Chou, Julian Katz-Samuels, Sean Culatana, Peter Bailis, Alexander C. Berg, Robert Nowak, Roshan Sumbaly, Matei Zaharia, I. Zeki Yalniz | Similarity Search for Efficient Active Learning and Search of Rare Concepts |
| 2022 | Xufeng Cai, Chaobing Song, Cristobal Guzman, Jelena Diakonikolas | Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems, |
| 2022 | Jimmy Wu, Yatong Chen and Yang Liu | Metric-Fair Classifier Derandomization |
| 2022 | Jialu Wang, Eric Xin Wang and Yang Liu | Understanding Instance-Level Impact of Fairness Constraints |
| 2022 | Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, and Tongliang Liu | Estimating Instance-dependent Label-noise Transition Matrix using a Deep Neural Network |
| 2022 | Brett Sargent, Mohammad Jafari, Giovanny Marquez, Abijeet Singh Mehta, Yao-Hui Sun, Hsin-ya Yang, Kan Zhu, Roslyn Rivkah Isseroff, Min Zhao, and Marcella Gomez | A machine learning based model accurately predicts cellular response to electric fields in multiple cell types |
| 2022 | Camilo Garcia Trillos, Nicolas Garcia Trillos | On the regularized risk of distributionally robust learning over deep neural networks |
| 2022 | Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha | Towards Evaluating the Robustness of Neural Networks Learned by Transduction |
| 2022 | Zhenmei Shi, Jenny Wei, Yingyu Liang | A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features |
| 2022 | Yuchen Zeng, Hongxu Chen, Kangwook Lee | Improving Fairness via Federated Learning |
| 2022 | Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee | LIFT: Language-Interfaced FineTuning for Non-Language Machine Learning Tasks |
| 2022 | Changhun Jo, Jy-yong Sohn, Kangwook Lee | Breaking Fair Binary Classification with Optimal Flipping Attacks |
| 2022 | Ahmet Alacaoglu, Hanbaek Lyu | Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data |
| 2022 | Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaid Harchaoui | Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates |
| 2022 | Hanbaek Lyu, Christopher Strohmeier, Deanna Needell | Online nonnegative tensor factorization and CP-Dictionary Learning for Markovian data |
| 2022 | Brandon Legried, Erin K. Molloy, Tandy Warnow, and S ebastien Roch | Polynomial-time statistical estimation of species trees under gene duplication and loss |
| 2022 | Max Hill and Sebastien Roch | On the effect of intralocus recombination on triplet-based species tree estimation |
| 2022 | Varun Embar, Sriram Srinivasan, and Lise Getoor | Learning Explainable Templated Graphical Models |
| 2022 | Connor Pryor, Charles Andrew Dickens, Eriq Augustine, Alon Albalak, William Yang Wang, and Lise Getoor | NeuPSL: Neural Probabilistic Soft Logic |
| 2022 | Zhenlin Wang, Andrew Wagenmaker, Kevin Jamieson | Best Arm Identification with Safety Constraints |
| 2022 | Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson | Beyond No Regret: Instance-Dependent PAC Reinforcement Learning |
| 2022 | Yifang Chen, Simon S. Du, Kevin Jamieson | Active Multi-Task Representation Learning |
| 2022 | Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson | First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach |
| 2022 | Jennifer Brennan, Lalit Jain, Sofia Garman, Ann E Donnelly, Kevin Jamieson, Erik Scott Wright | Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
| 2022 | Damek Davis, Dmitriy Drusvyatskiy, Yin-Tat Lee, Swati Padmanabhan, Guanghao Ye | A gradient sampling algorithm with complexity guarantees for Lipschitz functions in high and low dimensions |
| 2022 | Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff | Multiplayer performative prediction: learning in decision dependent games |
| 2022 | Damek Davis, Dmitriy Drusvyatskiy, Liwei Jiang | Subgradient methods near active manifolds: saddle point avoidance, local convergence, and asymptotic normality |
| 2022 | Yinglun Zhu, and Robert Nowak | Pareto Optimal Model Selection in Linear Bandits |
| 2022 | Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, and Henry Hoffman | NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. |
| 2022 | Greg Ongie and Rebecca Willett | The Role of Linear Layers in Nonlinear Interpolating Networks |
| 2022 | Ruoxi Jiang and Rebecca Willett | Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification |
| 2022 | Yue Gao, Abby Stevens, Garvesh Raskutti, Rebecca Willett | azy Estimation of Variable Importance for Large Neural Networks |
| 2022 | Daren Wang, Yi Yu, Rebecca Willett | Detecting abrupt changes in high-dimensional self-exciting Poisson processes |
| 2022 | Yuming Chen, Daniel Sanz-Alonso, and Rebecca Willett | Autodifferentiable Ensemble Kalman Filters |
| 2022 | Punit Gandhi, Lily Liu, and Mary Silber | A Pulsed-Precipitation Model of Dryland Vegetation Pattern Formation |
| 2022 | Ni, Z., Prasad, A., Chen, S., Halberg, R.B., Arkin, L.M., Drolet, B.A., Newton, M.A. and Kendziorski, C. | SpotClean adjusts for spot swapping in spatial transcriptomics data |
| 2022 | Yu, P., Ericksen, S., Gitter, A. and Newton, M.A. | Bayes optimal informer sets for early_stage drug discovery |
| 2022 | Ng, T.L. and Newton, M.A. | Random weighting in LASSO regression |
| 2022 | Parhi, Rahul, and Robert D. Nowak | What kinds of functions do deep neural networks learn? Insights from variational spline theory |
| 2022 | Parhi, Rahul, and Robert D. Nowak | Near-minimax optimal estimation with shallow ReLU neural networks |
| 2022 | Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas | Robust Sparse Mean Estimation via Sum of Squares |
| 2022 | Rina Foygel Barber, Emmanuel J. Cands, Aaditya Ramdas, and Ryan Tibshirani | Permutation tests using arbitrary permutation distributions. |
| 2022 | Rina Foygel Barber, Mathias Drton, Nils Sturma, and Luca Weihs | Half-trek criterion for identifiability of latent variable models |
| 2022 | Rina Foygel Barber, Emmanuel J. Cands, Aaditya Ramdas, and Ryan Tibshirani | Conformal prediction beyond exchangeability |
| 2022 | Zhimei Ren and Rina Foygel Barber | Derandomized Knockoffs: Leveraging E-values for False Discovery Rate Control |
| 2022 | Michael Bian and Rina Foygel Barber | Training-conditional coverage for distribution-free predictive inference. (Code. |
| 2022 | Timothy Duff, Anton Leykin, Jose Israel Rodriguez | u-generation: solving systems of polynomials equation-by-equation |
| 2022 | Laurentiu G. Maxim, Jose Israel Rodriguez, Botong Wang, Lei Wu | Logarithmic cotangent bundles, Chern-Mather classes, and the Huh-Sturmfels Involution conjecture |
| 2022 | Emil Horobet, Jose Israel Rodriguez | Data loci in algebraic optimization |
| 2022 | Laurentiu G. Maxim, Jose Israel Rodriguez, Botong Wang | A Morse theoretic approach to non-isolated singularities and applications to optimization |
| 2022 | Adhyyan Narang, Omid Sadeghi, Lillian J Ratliff, Maryam Fazel, Jeff Bilmes | Interactive Combinatorial Bandits: Balancing Competitivity and Complementarity |
| 2022 | Mitas Ray, Lillian J Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel | Decision-dependent risk minimization in geometrically decaying dynamic environments |
| 2022 | Sarah Dean, Mihaela Curmei, Lillian J Ratliff, Jamie Morgenstern, Maryam Fazel | Multi-learner risk reduction under endogenous participation dynamics |
| 2022 | Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S Du | Learning in Congestion Games with Bandit Feedback |
| 2022 | Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian Ratliff | Learning in Stochastic Monotone Games with Decision-Dependent Data |
| 2022 | Vincent Roulet, Siddhartha Srinivasa, Maryam Fazel, Zaid Harchaoui | Complexity Bounds of Iterative Linear Quadratic Optimization Algorithms for Discrete Time Nonlinear Control |
| 2022 | Vincent Roulet, Siddhartha Srinivasa, Maryam Fazel, Zaid Harchaoui | Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates |
| 2022 | Yang Zheng, Yue Sun, Maryam Fazel, Na Li | Escaping High-order Saddles in Policy Optimization for Linear Quadratic Gaussian (LQG) Control |
| 2022 | Yue Sun, Samet Oymak, Maryam Fazel | System Identification via Nuclear Norm Regularization |
| 2022 | Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J Ratliff | Multiplayer performative prediction: Learning in decision-dependent games |
| 2022 | Dohyun Kwon, Ying Fan, and Kangwook Lee
| Score-based generative modeling secretly minimizes the Wasserstein distance
|
| 2022 | Vivak Patel | Stopping criteria for, and strong convergence of, stochastic gradient descent on Bottou-Curtis-Nocedal functions |
| 2022 | Vivak Patel, Shushu Zhang, Bowen Tian | Global Convergence and Stability of Stochastic Gradient Descent |
| 2022 | Andrew Wagenmaker, Kevin Jamieson | Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design |
| 2022 | Zhaoqi Li, Lillian Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain | Instance-optimal PAC Algorithms for Contextual Bandits |
| 2022 | Yunyi Shen, Sameer Deshpande | On the posterior contraction of the multivariate spike-and-slab LASSO |
| 2022 | Yunyi Shen, Claudia Solis-Lemus, Sameer Deshpande | Sparse Gaussian chain graphs with the spike-and-slab LASSO |
| 2022 | Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu | BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach |
| 2022 | Greg Canal, Blake Mason, Ramya Korlakai Vinayak, Robert Nowak | One for All: Simultaneous Metric and Preference Learning over Multiple Users |
| 2022 | Ilias Diakonikolas, Daniel Kane, Jasper C.H. Lee and Ankit Pensia | Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions |
| 2022 | Ni, Z, Prasad, A, Chen, S, Halberg, RB, Arkin, L, Drolet, B, Newton, MA and Kendziorski, | SpotClean adjusts for spot swapping in spatial transcriptomics data |
| 2022 | Luo, Y. and Garc’a Trillos, N. | Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective |
| 2022 | Mehmet F Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang | Attentive Walk-Aggregating Graph Neural Networks |
| 2022 | Liwei Jiang, Yudong Chen, and Lijun Ding | Algorithmic Regularization in Model-free Overparametrized Asymmetric Matrix Factorization |
| 2022 | Ahmet Alacaoglu, Yura Malitsky | Stochastic variance reduction for variational inequality methods |
| 2022 | Ahmet Alacaoglu, Luca Viano, Niao He, Volkan Cevher | A natural actor-critic framework for zero-sum Markov games
|
| 2022 | Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher | On the Convergence of Stochastic Primal-Dual Hybrid Gradient |
| 2022 | Yinglun Zhu, Robert Nowak | Efficient Active Learning with Abstention |
| 2022 | Yinglun Zhu, Robert Nowak | Active Learning with Neural Networks: Insights from Nonparametric Statistics |
| 2023 | O'Neill, M. and Wright, S. J. | A Line-search descent algorithm for strict saddle functions with complexity guarantees |
| 2023 | Y Xie, SJ Wright | Complexity of projected Newton methods for bound-constrained optimization |
| 2023 | Jingcheng Xu, CŽcile AnŽ | Identifiability of local and global features of phylogenetic networks from average distances |
| 2023 | Benjamin Teo, Jeffrey P. Rose, Paul Bastide, CŽcile AnŽ | Accounting for within-species variation in continuous trait evolution on a phylogenetic network |
| 2023 | Nicolas Garcia Trillos, Pengfei He, and Chenghui Li | Large sample spectral analysis of graph-based multi-manifold clustering |
| 2023 | Leon Bungert, Nicolas Garcia Trillos, Ryan Murray | The Geometry of Adversarial Training in Binary Classification |
| 2023 | Nicolas Garcia Trillos, Matt Jacobs, and Jakwang Kim | The multimarginal optimal transport formulation of adversarial multiclass classification |
| 2023 | Vivak Patel, Mohammad Jahangoshahi, Daniel Adrian Maldonado | Randomized Block Adaptive Linear System Solvers |
| 2023 | Nathaniel Pritchard, Vivak Patel | Towards Practical Large-scale Randomized Iterative Least Squares Solvers through Uncertainty Quantification |
| 2023 | Sameer Deshpande | flexBART: Flexible Bayesian regression trees with categorical predictors |
| 2023 | Rudy Geelen, Stephen Wright, and Karen Willcox | Operator inference for non-intrusive model reduction with quadratic manifolds |
| 2023 | Matteo Croci, Karen Willcox, and Stephen Wright | Multi-output multilevel best linear unbiased estimators via semidefinite programming |
| 2023 | Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, and Robert Nowak | A Fully first-order method for stochastic bilevel optimization |
| 2023 | Like Hui, Mikhail Belkin, and Stephen Wright | Cut your losses with squentropy |
| 2023 | Xufeng Cai, Chaobing Song, Stephen Wright, Jelena Diakonikolas | Cyclic block coordinate descent with variance reduction for composite nonconvex optimization |
| 2023 | Changyu Gao and Stephen Wright | Differentially private optimization for smooth nonconvex ERM |
| 2023 | John Fogg, Elizabeth S. Allman, CŽcile AnŽ | PhyloCoalSimulations: A simulator for network multispecies coalescent models, including a new extension for the inheritance of gene flow |
| 2023 | Lauren Frankel, CŽcile AnŽ | Summary tests of introgression are highly sensitive to rate variation across lineages |
| 2023 | Shivam Gupta, Jasper C.H. Lee and Eric Price | High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors |
| 2023 | Shivam Gupta, Jasper C.H. Lee and Eric Price | Finite-Sample Symmetric Mean Estimation with Fisher Information Rate |
| 2023 | Ilias Diakonikolas, Daniel Kane, Jasper C.H. Lee, Ankit Pensia and Thanasis Pittas | A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm |
| 2023 | McCoy, S, Shelef, M, Zheng, Z, and Newton, MA | NOVEL AUTO-ANTIBODIES AND METHOD TO DETECT SJ…GREN'S DISEASE |
| 2023 | Hao Yan and Keith Levin | Minimax rates for latent position estimation in the generalized random dot product graph |
| 2023 | Ajinkya Kokandakar, Hyunseung Kang, and Sameer Deshpande | Bayesian causal forests and the 2022 ACIC Data Challenge: Scalability and sensitivity. |
| 2023 | Young Wu, Jeremy McMahan, Xiaojin Zhu, and Qiaomin Xie | Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning |
| 2023 | Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha. | The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning |
| 2023 | Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha. | Stratified Adversarial Robustness with Rejection |
| 2023 | Lijun Ding and Alex L. Wang | Sharpness and well-conditioning of nonsmooth convex formulations in statistical signal recovery |
| 2023 | Ying Fan, Kangwook Lee | Optimizing DDPM Sampling with Shortcut Fine-Tuning |
| 2023 | Young Wu, Jeremy McMahan, Xiaojin Zhu, and Qiaomin Xie | On Faking a Nash Equilibrium |
| 2023 | Le, Phong V. V., James T. Randerson, Rebecca Willett, Stephen Wright, Padhraic Smyth, ClŽment Guilloteau, Antonios Mamalakis & Efi Foufoula-Georgiou | Climate-driven changes in the predictability of seasonal precipitation |
| 2023 | Suzanna Parkinson, Greg Ongie, Rebecca Willett | Linear Neural Network Layers Promote Learning Single- and Multiple-Index Models |
| 2023 | Raphael Rossellini, Rina Foygel Barber, Rebecca Willett | Integrating Uncertainty Awareness into Conformalized Quantile Regression |
| 2023 | Yue Gao, Garvesh Raskutti, Rebecca Willett | Fast, Distribution-free Predictive Inference for Neural Networks with Coverage Guarantees. |
| 2023 | Yonghoon Lee, Rina Foygel Barber, Rebecca Willett | Distribution-free inference with hierarchical data |
| 2023 | Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett | Training neural operators to preserve invariant measures of chaotic attractors. |
| 2023 | Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett | Deep Stochastic Mechanics |
| 2023 | Jake A. Soloff, Rina Foygel Barber, Rebecca Willett | Bagging Provides Assumption-free Stability |
| 2023 | Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett. | Reduced-Order Autodifferentiable Ensemble Kalman Filters |
| 2023 | Elena Orlova, Haokun Liu, Raphael Rossellini, Benjamin Cash, Rebecca Willett | Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting |
| 2023 | Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie | VISER: A Tractable Solution Concept for Games with Information Asymmetry |
| 2023 | Ilias Diakonikolas, Sushrut Karmalkar, Jongho Park, Christos Tzamos | Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions |
| 2023 | Andrew Wagenmaker, Aldo Pacchiano | Leveraging Offline Data in Online Reinforcement Learning |
| 2023 | Andrew Wagenmaker, Dylan Foster | Instance Optimality in Interactive Decision Making: Toward a Non-Asymptotic Theory |
| 2023 | Jillian Fisher,ÊLang Liu,ÊKrishna Pillutla,ÊYejin Choi,ÊZaid Harchaoui | Influence Diagnostics under Self-concordance |
| 2023 | Ronak Mehta,ÊVincent Roulet,ÊKrishna Pillutla,ÊLang Liu,ÊZaid Harchaoui | Stochastic Optimization for Spectral Risk Measures |
| 2023 | Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor | Reward-Mixing MDP with Few Latent Contexts are Learnable |
| 2023 | C. Liu, D. Drusvyatskiy, M. Belkin, D. Davis, Y.-A. Ma | Aiming towards the minimizers: fast convergence of SGD for overparametrized problems |
| 2023 | Dmitriy Drusvyatskiy, Joshua Cutler, Mateo Diaz | Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality |
| 2023 | Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff | Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games |
| 2023 | Yiping Wang, Yifang Chen, Simon Du, Kevin Jamieson | Improved Active Multi-Task Representation Learning via Lasso |
| 2023 | Andrew Wagenmaker, Guanya Shi, Kevin Jamieson | Optimal Exploration for Model-Based RL in Nonlinear Systems |
| 2023 | Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff | Logarithmic Regret for Matrix Games against an Adversary with Noisy Bandit Feedback |
| 2023 | Yu Gui, Rohan Hore, Zhimei Ren, and Rina Foygel Barber | Conformalized survival analysis with adaptive cutoffs. |
| 2023 | Young-Joo Yun and Rina Foygel Barber | Selective inference for clustering with unknown variance |
| 2023 | Yuetian Luo, Zhimei Ren, Rina Foygel Barber | Iterative Approximate Cross-Validation |
| 2023 | Rina Foygel Barber, Emmanuel J. Cands, Aaditya Ramdas, and Ryan Tibshirani | De FinettiÕs Theorem and Related Results for Infinite Weighted Exchangeable Sequences. |
| 2023 | Yu Gui, Rina Foygel Barber, and Cong Ma | Conformalized matrix completion. |
| 2023 | Max Hill and Sebastien Roch | Inconsistency of triplet-based and quartet-based species tree estimation under intralocus recombination |
| 2023 | Yasamin Tabatabaee, Sebastien Roch, and Tandy Warnow | Statistically consistent rooting of species trees under the multispecies coalescent model |
| 2023 | Zhihan Xiong, Roqui Shen, Qiwen Cui, Maryam Fazel, Simon S. Du | Near-Optimal Randomized Exploration for Tabular Markov Decision Processes |
| 2023 | Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S. Du | Offline congestion games: How feedback type affects data coverage requirement |
| 2023 | Zhaolin Ren, Yang Zheng, Maryam Fazel, Na Li | On Controller Reduction in Linear Gaussian Control with Performance Bounds |
| 2023 | Omid Sadeghi, Maryam Fazel | Fast First-Order Methods for Monotone Strongly DR-Submodular Maximization |
| 2023 | Yuzhen Qin, Yingcong Li , Fabio Pasqualetti, Maryam Fazel, Samet Oymak | Stochastic Contextual Bandits with Long Horizon Rewards |
| 2023 | Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, Tamer Ba_ar | Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies |
| 2023 | Lijun Ding, Dmitriy Drusvyatskiy, Maryam Fazel, Zaid Harchaoui | Flat Minima Generalize for Low-rank Matrix Recovery |
| 2023 | Omid Sadeghi, Maryam Fazel | No-regret Online Prediction with Strategic Experts |
| 2023 | Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S. Du | A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning |
| 2023 | Avinandan Bose, Mihaela Curmei, Daniel Jiang, Jamie Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel | Preference-Aware Initialization for Multi-learner Systems: Algorithm and Analysis. |
| 2023 | Zhihan Xiong, Romain Camilleri, Maryam Fazel, Lalit Jain, Kevin Jamieson | A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity |
| 2023 | Bernstein MN, Ni Z, Prasad A, Brown J, Mohanty C, Stewart R, Newton MA, Kendziorski C. | SpatialCorr identifies gene sets with spatially varying correlation structure.Ê |
| 2023 | Ahmet Alacaoglu, Axel Bšhm, Yura Malitsky | Beyond the golden ratio for variational inequality algorithms |
| 2023 | Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert Nowak
| Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
|
| 2023 | Jifan Zhang, Shuai Shao, Saurabh Verma, Robert Nowak
| Algorithm selection for deep active learning with imbalanced datasets
|
| 2023 | Shyam Nuggehalli, Jifan Zhang, Lalit Jain, Robert Nowak
| Direct: Deep active learning under imbalance and label noise
|
| 2023 | Liu Yang, Kangwook Lee, Robert Nowak, Dimitris Papailiopoulos
| Looped Transformers are Better at Learning Learning Algorithms
|
| 2023 | Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M Pawan Kumar, Emilien Dupont, Francisco JR Ruiz, Jordan S Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi | Mathematical discoveries from program search with large language models |
| 2023 | Rahul Parhi, Robert D Nowak | Deep learning meets sparse regularization: A signal processing perspective
|
| 2023 | Jeongyeol Kwon, Dohyun Kwon, Steve Wright, Robert Nowak
| On penalty methods for nonconvex bilevel optimization and first-order stochastic approximation
|
| 2023 | Ronald DeVore, Robert D Nowak, Rahul Parhi, Jonathan W Siegel
| Weighted variation spaces and approximation by shallow ReLU networks
|
| 2023 | Joseph Shenouda, Rahul Parhi, Robert D. Nowak | A Continuous Transform for Localized Ridgelets
|
| 2023 | Danica Fliss, Willem Marais, Robert D Nowak
| Filtered Iterative Denoising for Linear Inverse Problems
|
| 2023 | Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert D Nowak, Yixuan Li
| Feed two birds with one scone: Exploiting wild data for both out-of-distribution generalization and detection
|
| 2023 | Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, and Stephen Wright. | Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing |
| 2023 | Shubham Kumar Bharti, Stephen Wright, Adish Singla, Xiaojin Zhu | Optimally Teaching a Linear Behavior Cloning Agent |
| 2023 | Lijun Ding, Stephen J Wright | On Squared-Variable Formulations |
| 2023 | Shi Chen, Zhiyan Ding, Qin Li, Stephen J Wright | On optimal bases for multiscale PDEs and Bayesian homogenization |
| 2023 | Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis | Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise |
| 2023 | Chaobing Song and Jelena Diakonikolas | Cyclic Coordinate Dual Averaging with Extrapolation |
| 2023 | Ilias Diakonikolas, Jelena Diakonikolas, Daniel M Kane, Puqian Wang, Nikos Zarifis | Information-Computation Tradeoffs for Learning Margin
Halfspaces with Random Classification Noise |
| 2023 | Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas | Robustly Learning a Single Neuron via Sharpness |
| 2023 | Zhuohang Li, Andrew Lowy, Jing Liu, Toshiaki Koike-Akino, Bradley Malin, Kieran Parsons, Ye Wang | Exploring User-Level Gradient Inversion with a Diffusion Prior |
| 2023 | Yifang Chen, Yingbing Huang, Simon Shaolei Du, Kevin Jamieson, Guanya Shi | Active representation learning for general task space with applications in robotics |
| 2023 | Andrew Wagenmaker, Guanya Shi, Kevin Jamieson | Optimal Exploration for Model-Based RL in Nonlinear Systems |
| 2023 | Vivak Patel | Counterexamples for Noise Models of Stochastic Gradients |
| 2023 | Sebastien Roch | Expanding the Class of Global Objective Functions for Dissimilarity-Based Hierarchical Clustering |
| 2023 | Yasamin Tabatabaee, Sebastien Roch, and Tandy Warnow | QR-STAR: A Polynomial-Time Statistically Consistent Method for Rooting Species Trees Under the Coalescent |
| 2023 | Wanrong Zhu and Rina Foygel Barber. | Approximate co-sufficient sampling with regularization. |
| 2023 | Rohan Hore and Rina Foygel Barber. | Conformal prediction with local weights: randomization enables robust guarantees. |
| 2023 | Ruiting Liang and Rina Foygel Barber. | Algorithmic stability implies training-conditional coverage for distribution-free prediction methods. |
| 2023 | Shi Chen, Zhiyan Ding, Qin Li and Leonardo Zepeda-Nunez | High-frequency limit of the inverse scattering problem: asymptotic convergence from inverse Helmholtz to inverse Liouville |
| 2023 | Utkarsh Ojha, Yuheng Li, Anirudh Sundara Rajan, Yingyu Liang, Yong Jae Lee | Dissecting Knowledge Distillation: An Exploration of its Inner Workings and Applications |
| 2023 | Zhenmei Shi, Jenny Wei, Yingyu Liang | Provable Guarantees for Neural Networks via Gradient Feature Learning |
| 2023 | Joowon Lee, Hanbaek Lyu, and Weixin Yao | Interpretable Feature Extraction by Supervised Dictionary Learning for Identification of Cancer-Associated Gene Clusters |
| 2023 | Hardeep Bassi, Richard Yim, Rohith Kodukula, Joshua Vendrow, Cherlin Zhu, Hanbaek Lyu | Learning to predict synchronization of coupled oscillators on heterogeneous graphs |
| 2023 | Joowon Lee, Hanbaek Lyu, and Weixin Yao | Exponentially Convergent Algorithms for Supervised Matrix Factorization |
| 2023 | Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu | Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization |
| 2023 | Chenghui Li, Rishi Sonthalia, Nicolas Garcia Trillos | Spectral Neural Networks: Approximation Theory and Optimization Landscape
|
| 2023 | Nicolas Garcia Trillos, Melanie Weber | Continuum Limits of Ollivier's Ricci Curvature on data clouds: pointwise consistency and global lower bounds |
| 2023 | Yiding Chen, Xiaojin Zhu, and Kirthevasan Kandasamy | Mechanism design for collaborative normal mean estimation |
| 2024 | S Chen, Z Ding, Qin Li, SJ Wright | A reduced order Schwarz method for nonlinear multiscale elliptic equations based on two-layer neural networks |
| 2024 | K. D. Levin and B. Betancourt | Fast Generation of Exchangeable Sequences of Clusters Data |
| 2024 | Nathaniel Pritchard, Vivak Patel | Residual Tracking and Stopping for Iterative Random Sketching |
| 2024 | Vivak Patel, Albert Berahas | Gradient descent in the absence of global Lipschitz continuity of the gradients |
| 2024 | Garc’a Trillos, C. and Garc’a Trillos, N. | On adversarial robustness and the use of Wasserstein ascent-descent dynamics to enforce it |
| 2024 | Garc’a Trillos, N. and Jacobs, M. and Kim, J. | On the existence of solutions to adversarial training in multiclass classification |
| 2024 | Carrillo, J.A. and Garc’a Trillos, N. and Li, S. and Zhu, Y. | FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization |
| 2024 | Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak | Vector-Valued Variation Spaces and Widths Bounds for DNNs: Insights on Weight Decay Regularization |
| 2024 | CŽcile AnŽ, John Fogg, Elizabeth S. Allman, Hector Ba–os, John A. Rhodes | Anomalous networks under the multispecies coalescent: theory and prevalence |
| 2024 | Joseph Shenouda, Yamin Zhou, Robert Nowak | ReLUs are Sufficient for Learning Implicit Neural Representations |
| 2024 | Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Stephen Mussmann, Yinglun Zhu, Jeff Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D Nowak | Labelbench: A comprehensive framework for benchmarking adaptive label-efficient learning |
| 2024 | Subhojyoti Mukherjee, Qiaomin Xie, Josiah P Hanna, Robert Nowak
| Speed: Experimental design for policy evaluation in linear heteroscedastic bandits
|
| 2024 | Jeongyeol Kwon, Liu Yang, Robert Nowak, Josiah Hanna
| Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments
|
| 2024 | Nasim Soltani, Jifan Zhang, Batool Salehi, Debashri Roy, Robert Nowak, Kaushik Chowdhury
| Learning from the Best: Active Learning for Wireless Communications
|
| 2024 | Gantavya Bhatt, Yifang Chen, Arnav M Das, Jifan Zhang, Sang T Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey Bilmes, Simon S Du, Kevin Jamieson, Jordan T Ash, Robert D Nowak | An experimental design framework for label-efficient supervised finetuning of large language models |
| 2024 | Ziqian Lin and Kangwook Lee | Dual Operating Modes of In-Context Learning |
| 2024 | Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee | Memorization Capacity for Additive Fine-Tuning |
| 2024 | Yuchen Zeng and Kangwook Lee | The Expressive Power of Low-Rank Adaptation |
| 2024 | Peizhe Li, Jimmy Vineyard, Seungyeon Oh, Jack Maloney, Amy L. Cochran, and Haley Colgate Kottler | Integrating Local Learning into the Two-Stage Markov Task to Separate Model-Based from Model-Free Learning |
| 2024 | Damek Davis,ÊDmitriy Drusvyatskiy, Liwei Jiang | Asymptotic normality and optimality in nonsmooth stochastic approximation |
| 2024 | Damek Davis,ÊDmitriy Drusvyatskiy, Liwei Jiang | Active, manifolds, stratifications, and convergence to local minima in nonsmooth optimization |
| 2024 | Adityanarayanan Radhakrishnan,ÊMikhail Belkin,ÊDmitriy Drusvyatskiy | Linear Recursive Feature Machines provably recover low-rank matrices |
| 2024 | Joshua Cutler, Mateo D’az, Dmitriy Drusvyatskiy | The radius of statistical efficiency |
| 2024 | Ahmet Alacaoglu, Stephen J. Wright | Complexity of single loop algorithms for nonlinear programming with stochastic objective and constraints. |
| 2024 | Andrew Lowy, Jonathan Ullman, and Stephen J. Wright. | How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization |
| 2024 | Ahmet Alacaoglu, Donghwan Kim, Stephen J. Wright. | Extending the Reach of First-Order Algorithms for Nonconvex Min-Max Problems with Cohypomonotonicity |
| 2024 | Charles Dickens, Changyu Gao, Connor Pryor, Stephen Wright, Lise Getoor | Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning. |
| 2024 | Ruhui Jin, Martin Guerra, Qin Li, Stephen Wright | Optimal experimental design via gradient flow |
| 2024 | Shuyao Li, Stephen J Wright | A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees |
| 2024 | Ronak Mehta, Jelena Diakonikolas, Zaid Harchaoui | A Primal-Dual Algorithm for Faster Distributionally Robust Optimization |
| 2024 | Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas | Robustly Learning Single-Index Models via Alignment Sharpness |
| 2024 | Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas | Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions |
| 2024 | Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J. Wright | Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses |
| 2024 | Andrew Lowy, Zeman Li, Tianjian Huang, Meisam Razaviyayn | Optimal Differentially Private Model Training with Public Data |
| 2024 | Jing Liu, Andrew Lowy, Toshiaki Koike-Akino, Kieran Parsons, Ye Wang | Efficient Differentially Private Fine-Tuning of Diffusion Models |
| 2024 | Andrew Lowy, Zhuohang Li, Jing Liu, Toshiaki Koike-Akino, Kieran Parsons, Ye Wang | Why Does Differential Privacy with Large Epsilon Prevent Practical Membership Inference Attacks? |
| 2024 | Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson | Fair Active Learning in Low-Data Regimes |
| 2024 | Zhaoqi Li, Kevin Jamieson, Lalit Jain | Optimal Exploration is no harder than Thompson Sampling |
| 2024 | Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff | Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits |
| 2024 | Zhihan Xiong, Romain Camilleri, Maryam Fazel, Lalit Jain, Kevin Jamieson | A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity |
| 2024 | Hao Yan and Keith Levin | Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models |
| 2024 | Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu
| On The Complexity of First-Order methods for Stochastic Bilevel Optimization |
| 2024 | Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis | Prospective Side Information for Latent MDPs
|
| 2024 | Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni | RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation
|
| 2024 | Brandon Legried, Sebastien Roch | Pairwise sequence alignment at arbitrarily large evolutionary distance |
| 2024 | Sebastien Roch | Modern Discrete Probability: An Essential Toolkit |
| 2024 | Vasileios Charisopoulos, Rebecca Willett | Nonlinear tomographic reconstruction via nonsmooth optimization |
| 2024 | Jake A. Soloff, Rina Foygel Barber, Rebecca Willett | Building a stable classifier with the inflated argmax |
| 2024 | Owen Melia, Olivia Tsang, Vasileios Charisopoulos, Yuehaw Khoo, Jeremy Hoskins, Rebecca Willett | Multi-Frequency Progressive Refinement for Learned Inverse Scattering |
| 2024 | Melissa Adrian, Daniel Sanz-Alonso, Rebecca Willett | Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet |
| 2024 | Jake A. Soloff, Rina Foygel Barber, Rebecca Willett | Stability via resampling: statistical problems beyond the real line |
| 2024 | Aabesh Bhattacharyya and Rina Foygel Barber. | Group-Weighted Conformal Prediction. |
| 2024 | Anastasios N. Angelopoulos, Rina Foygel Barber, and Stephen Bates. | Online conformal prediction with decaying step sizes |
| 2024 | Yuetian Luo and Rina Foygel Barber. | The Limits of Assumption-free Tests for Algorithm Performance. |
| 2024 | Rina Foygel Barber. | Hoeffding and Bernstein inequalities for weighted sums of exchangeable random variables. |
| 2024 | Yuetian Luo and Rina Foygel Barber. | Is algorithmic stability testable? A unified framework under computational constraints. |
| 2024 | Ran Xie, Rina Foygel Barber, and Emmanuel Cands | Boosted Conformal Prediction Intervals. |
| 2024 | Borong Zhang, Leonardo Zepeda-Nœ–ez, Qin Li | Solving the wide-band inverse scattering problem via equivariant neural networks |
| 2024 | Zhuoyan Xu, Zhenmei Shi, Junyi Wei, Fangzhou Mu, Yin Li, Yingyu Liang. | Towards Few-shot Adaptation of Foundation Models via Multitask Finetuning |
| 2024 | Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha. | Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection |
| 2024 | Zhenmei Shi, Zhuoyan Xu, Junyi Wei, Yingyu Liang. | Why Larger Language Models Do In-context Learning Differently? |
| 2024 | Yixuan Zhang, Lucy Huo, Yudong Chen, and Qiaomin Xie | Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA |
| 2024 | Brahma S. Pavse, Matthew Zurek, Yudong Chen, Qiaomin Xie, Josiah P. Hanna | Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces |
| 2024 | Matthew Zurek, Yudong Chen | Gap-Free Clustering: Sensitivity and Robustness of SDP |
| 2024 | Matthew Zurek, Yudong Chen | Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs |
| 2024 | Hanbaek Lyu | Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates |
| 2024 | Hanbaek Lyu, Yacoub Kureh, Joshua Vendrow, Mason A. Porter | Learning low-rank latent mesoscale structures in networks |
| 2024 | Keunsu Kim, Hanbaek Lyu, Jinsu Kim, Jae-Hun Jung, | Supervised low-rank semi-nonnegative matrix factorization with frequency regularization for forecasting spatio-temporal data. |
| 2024 | Jianhao Peng, Chao Pan, Hanbaek Lyu, Minji Kim, Albert Cheng, and Olgica Milenkovic | Inferring Single-Molecule Chromatin Interactions via Online Convex Network Dictionary Learning |
| 2024 | Vishal Rana, Jianhao Peng, Chao Pan, Hanbaek Lyu, Albert Cheng, Minji Kim, and Olgica Milenkovic | Interpretable online network dictionary learning for inferring long-range chromatin interactions |
| 2024 | Lara Kassab, Alona Kryshchenko, Hanbaek Lyu, Denali Molitor, Deanna Needell, Elizabeta Rebrova | Sparseness-constrained nonnegative tensor factorization for detecting topics at different time scales |
| 2024 | Joowon Lee, Hanbaek Lyu, and Weixin Yao | Supervised Matrix Factorization: Local Landscape Analysis and Applications |
| 2024 | William Powell and Hanbaek Lyu | Stochastic optimization with arbitrary recurrent data sampling |
| 2024 | Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu | On the Complexity of First-Order Methods in Stochastic Bilevel Optimization. |
| 2024 | Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu | Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms. |
| 2024 | Danny Duan and Hanbaek Lyu | A fast and efficient randomized quasi-Newton method |
| 2024 | Joel Lewis, Hanbaek Lyu, Pavlo Pylyavskyy, and Arnab Sen | Scaling limit of soliton lengths in a multicolor box-ball system |
| 2024 | Kimberly Affeld, Christian Dean, Matthew Junge, Hanbaek Lyu, Connor Panish, Lily Reeves, | Four-parameter coalescing ballistic annihilation |
| 2024 | Nicolas Garcia Trillos, Bodhisattva Sen | A New Perspective On Denoising Based On Optimal Transport |
| 2024 | Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Xiaojin Zhu, and Qiaomin Xie | Minimally modifying a Markov game to achieve any Nash Equilibrium and value |
| 2024 | Jingcheng Xu and CŽcile AnŽ | A consistent least-squares criterion for calibrating edge lengths in phylogenetic networks |
| 2024 | Chanwoo Lee and Miaoyan Wang | Statistical and Computational Efficiency for Smooth Tensor Estimation with Unknown Permutations |
| 2024 | Subhojyoti Mukherjee, Josiah P Hanna, Robert Nowak | SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP |
| 2024 | Jordan Ellenberg, Francois Charton, Adam Zsolt Wagner, Geordie Williamson | PatternBoost: Constructions in Mathematics with a Little Help from AI |
| 2024 | Nicol‡s Garc’a Trillos, Sixu Li, Konstantin Riedl, and Yuhua Zhu | CB2O: Consensus-Based Bi-Level Optimization |
| 2024 | Andrew Lowy, Daogao Liu, Hilal Asi | Faster Algorithms for User-Level Differentially Private Stochastic Convex Optimization |
| 2024 | Ethan Ewer, Daewon Chae, Thomas Zeng, Jinkyu Kim, Kangwook Lee | Entp: Encoder-only next token prediction. |
| 2025 | Alex Hayes, Mark Fredrickson, Keith Levin | Estimating network-mediated causal effects via spectral embeddings |
| 2025 | P Yu, Y Lian, C Zuleger, RJ Albertini, MR Albertini, & MA Newton | Surrogate selection oversamples expanded T cell clonotypes |
| 2025 | John A. Rhodes, Hector Ba–os, Jingcheng Xu, CŽcile AnŽ | Identifying circular orders for blobs in phylogenetic networks |
| 2025 | Benjamin Teo, Paul Bastide, CŽcile AnŽ | Leveraging graphical model techniques to study evolution on phylogenetic networks |
| 2025 | Michael Maxfield, Jingcheng Xu, CŽcile AnŽ | A dissimilarity measure for semidirected networks |
| 2025 | Shi Chen, Qin Li, Oliver Tse, Stephen J Wright | Accelerating optimization over the space of probability measures. |
| 2025 | Yuchen Li and Hanbaek Lyu | Block Majorization-Minimization with Diminishing Radius for Constrained Nonsmooth Nonconvex Optimization |
| 2025 | Hanbaek Lyu and Sumit Muhkerjee, | Large random matrices with given margins |
| 2025 | Sungwon Ahn, Matthew Junge, Hanbaek Lyu, Jacob Richey, Lily Reeves, and David Sivakoff | Diffusion-limited annihilating-coalescing systems. |
| 2025 | Rahul Choudhary and Hanbaek Lyu | Linear convergence of SinkhornÕs algorithm for generalized static Schršdinger bridge |
| 2025 | David Clancy Jr., Hanbaek Lyu, and Sebastien Roch | Sample complexity of branch-length estimation by maximum likelihood |
| 2025 | Lauren E. Frankel and CŽcile AnŽ | Low accuracy of complex admixture graph inference from f-statistics |
| 2025 | Jiaxin Hua, Jesse N. Weberb, Lauren E. Fuessc, Natalie C. Steineld, Daniel I. Bolnicke, and Miaoyan Wang | A spectral framework to map QTLs affecting joint differential networks of gene co-expression |
| 2025 | Ahmet Alacaoglu, Yura Malitsky, Stephen J Wright | Towards Weaker Variance Assumptions for Stochastic Optimization |
| 2025 | Lijun Ding and Stephen J Wright | On squared-variable formulations for nonlinear semidefinite programming |
| 2025 | Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J Wright | Optimal rates for robust stochastic convex optimization |
| 2025 | Ruhui Jin, Qin Li, Stephen O. Mussmann, and Stephen J Wright | Continuous nonlinear experimental optimal design with gradient flow |
| 2025 | Subhojyoti Mukherjee, Josiah P Hanna, Qiaomin Xie, Robert Nowak | Pretraining decision transformers with reward prediction for in-context multi-task structured bandit learning |
| 2025 | Subhojyoti Mukherjee, Qiaomin Xie, Robert Nowak | Multi-task Representation Learning for Fixed Budget Pure-Exploration in Linear and Bilinear Bandits |
| 2025 | Gokcan Tatli, Yi Chen, Blake Mason, Robert D. Nowak, Ramya K. Vinayak | Metric Learning in an RKHS |
| 2025 | Alex Clinton, Yiding Chen, Xiaojin Zhu, Kirthevasan Kandasamy | Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution |
| 2025 | Keran Chen, Alex Clinton, Kirthevasan Kandasamy | Contributor-Side Incentives in a Data Marketplace for Mean Estimation |
| 2025 | Michael O Harding, Kirthevasan Kandasamy | Balancing Performance and Costs in Best Arm Identification |
| 2025 | Alex Clinton, Thomas Zeng, Yiding Chen, Xiaojin Zhu, Kirthevasan Kandasamy | A CramŽr-von Mises Approach to Incentivizing Truthful Data Sharing |
| 2025 | Liu Yang, Ziqian Lin, Kangwook Lee, Dimitris Papailiopoulos, Robert Nowak | Task Vectors in In-Context Learning: Emergence, Formation, and Benefit |
| 2025 | Hao Yan and Keith Levin | Estimating Multiple Weighted Networks with Node-Sparse Differences and Shared Low-Rank Structure |
| 2025 | Hao Yan and Keith Levin | Improved dependence on coherence in eigenvector and eigenvalue estimation error bounds |
| 2025 | Haley Colgate Kottler and Amy Cochran | A simplified and robust proxy-based approach for overcoming unmeasured confounding in EHR studies |
| 2025 | Matthew Zurek, Yudong Chen | Faster Fixed-Point Methods for Multichain MDPs |
| 2025 | Matthew Zurek, Guy Zamir, Yudong Chen | Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL |
| 2025 | Matthew Zurek, Yudong Chen | The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis |
| 2025 | Matthew Zurek, Yudong Chen | Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL |
| 2025 | Jordan S. Ellenberg, Cristofero S. Fraser-Taliente, Thomas R. Harvey, Karan Srivastava, Andrew V. Sutherland | Generative Modeling for Mathematical Discovery |
| 2025 | Xiuyu Ma, Christina Kendziorski, Michael A Newton | Improving negative binomial mixing computations for multi-group differential expression analysis |
| 2025 | Shangyuan Yang, Kirthevasan Kandasamy | Mechanism Design for Pairwise Exchanges of Nonrivalrous Goods with Negative Externalities |
| 2025 | Yuefan Cao, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Jiahao Zhang | Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies |
| 2025 | Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song. | Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation Abilities |
| 2025 | Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, Yufa Zhou. | Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix |
| 2025 | Zhuoyan Xu, Khoi Duc Nguyen, Preeti Mukherjee, Saurabh Bagchi, Somali Chaterji, Yingyu Liang, Yin Li. | Learning to Inference Adaptively for Multimodal Large Language Models* |
| 2025 | Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Yufa Zhou. | Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective |
| 2025 | Jeongyeol Kwon, Luke Dotson, Yudong Chen, Qiaomin Xie | Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way |
| 2025 | Jongha Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun | Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing |
| 2025 | Nicol‡s Garc’a Trillos, Aditya Kumar Akash, Sixu Li, Konstantin Riedl, Yuhua Zhu | Defending against diverse attacks in federated learning through consensus-based bi-level optimization |
| 2025 | Nicol‡s Garc’a Trillos, Chenghui Li, Raghavendra Venkatraman | Minimax Rates for the Estimation of Eigenpairs of Weighted Laplace-Beltrami Operators on Manifolds |
| 2025 | Chenghui Li, Nicol‡s Garc’a Trillos, Housen Li, Leo Suchan | Central Limit Theorem for the Eigenvalues of Graph Laplacians on Data Clouds |
| 2025 | Andrew Lowy, Daogao Liu | Differentially Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates |
| 2025 | Devansh Gupta, A.S. Poornash, Andrew Lowy, Meisam Razaviyayn | A Stochastic Optimization Framework for Private and Fair Learning from Decentralized Learning |
| 2025 | Haley Kottler, Julia Lindberg, Jose Israel Rodriguez | Method of moments for Gaussian mixtures: Implementation and benchmarks |
| 2025 | Yixuan Zhang, Dongyan (Lucy) Huo, Yudong Chen, and Qiaomin Xie | A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression |
| 2025 | Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi GNVV, Sui Jiet Tay, Ramya Korlakai Vinayak, Frederic Sala | Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL |
| 2025 | Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas | Robustly Learning Monotone Generalized Linear Models via Data Augmentation |
| 2025 | Thomas Zeng, Shuibai Zhang, Shutong Wu, Christian Classen, Daewon Chae, Ethan Ewer, Minjae Lee, Heeju Kim, Wonjun Kang, Jackson Kunde, Ying Fan, Jungtaek Kim, Hyung Il Koo, Kannan Ramchandran, Dimitris Papailiopoulos, Kangwook Lee | VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data |
| 2025 | Libin Zhu, Damek Davis, Dmitriy Drusvyatskiy, Maryam Fazel | Iteratively reweighted kernel machines efficiently learn sparse functions |
| 2025 | Libin Zhu, Damek Davis, Dmitriy Drusvyatskiy, Maryam Fazel | Spectral norm bound for the product of random Fourier-Walsh matrices |
| 2025 | Mateo D’az, Dmitriy Drusvyatskiy, Jack Kendrick, Rekha R. Thomas | Invariant kernels: rank stabilization and generalization across dimensions |
| 2025 | Damek Davis, Dmitriy Drusvyatskiy, Liwei Jiang | Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth |
| 2025 | David Clancy Jr., Hanbaek Lyu, Sebastien Roch | Likelihood landscape of binary latent model on a tree |
| 2025 | David Clancy Jr., Hanbaek Lyu, Sebastien Roch, Allan Sly | Likelihood-Based Root State Reconstruction on a Tree: Sensitivity to Parameters and Applications |
| 2025 | Max Hill, Sebastien Roch | Lower Bounds on the Sample Complexity of Species Tree Estimation when Substitution Rates Vary Across Loci |
| 2023 | Joseph Shenouda; Rahul Parhi; Robert D. Nowak | A Continuous Transform for Localized Ridgelets |
| 2023 | Rahul Parhi; Robert D. Nowak | Deep learning meets sparse regularization: A signal processing perspective |
| 2023 | Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert Nowak
| Multi-task Representation Learning for Pure Exploration in Bilinear Bandits |
| 2023 | Jifan Zhang, Shuai Shao, Saurabh Verma, Robert Nowak
| Algorithm selection for deep active learning with imbalanced datasets |
| 2024 | Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Stephen Mussmann, Yinglun Zhu, Jeff Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D Nowak
| Labelbench: A comprehensive framework for benchmarking adaptive label-efficient learning |
| 2024 | Liu Yang, Kangwook Lee, Robert D Nowak, Dimitris Papailiopoulos
| Looped Transformers are Better at Learning Learning Algorithms |
| 2024 | Subhojyoti Mukherjee, Qiaomin Xie, Josiah P Hanna, Robert Nowak | Speed: Experimental design for policy evaluation in linear heteroscedastic bandits |
| 2024 | Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert D Nowak, Yixuan Li | Feed two birds with one scone: Exploiting wild data for both out-of-distribution generalization and detection |
| 2023 | Sijia Fang, Karl Rohe | T-Stochastic Graphs |
| 2024 | Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro | Depth Separation in Norm-Bounded Infinite-Width Neural Networks |
