| 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 “artificial intelligence—the revolution hasn’t 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 Õ(m/ε3.5)-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 | Sébastien 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 Tánczos, 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 Eliás, 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 | Mason, Blake, Lalit Jain, Ardhendu Tripathy, and Robert Nowak. | Finding All ε-Good Arms in Stochastic Bandits |
| 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 tensors–no 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 | Sébastien 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 | Gürbüzbalaban, 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, Jérôme 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 | Böhm, 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*(n3ψ2) 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 ℓ1-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 | Nicolas Garcia Trillos, Pengfei He, and Chenghui Li | Large sample spectral analysis of graph-based multi-manifold clustering |
| 2021 | Camilo Garcia Trillos, Nicolas Garcia Trillos | On the regularized risk of distributionally robust learning over deep neural networks |
| 2021 | Leon Bungert, Nicolas Garcia Trillos, Ryan Murray | The Geometry of Adversarial Training in Binary Classification |
| 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 Améndola, 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 |
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| 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 | S Chen, Z Ding, Qin Li, SJ Wright | A reduced order Schwarz method for nonlinear multiscale elliptic equations based on two-layer neural networks |
| 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 | Y Xie, SJ Wright | Complexity of projected Newton methods for bound-constrained optimization |
| 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 |
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| 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 | A 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 | Nicolas Garcia Trillos, Matt Jacobs, and Jakwang Kim | The multimarginal optimal transport formulation of adversarial multiclass classification |
| 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 | Joowon Lee, Hanbaek Lyu, and Weixin Yao | Interpretable Feature Extraction by Supervised Dictionary Learning for Identification of Cancer-Associated Gene Clusters |
| 2022 | Hardeep Bassi, Richard Yim, Rohith Kodukula, Joshua Vendrow, Cherlin Zhu, Hanbaek Lyu | Learning to predict synchronization of coupled oscillators on heterogeneous graphs |
| 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 |
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| 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_x0003_ |
| 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. Candès, 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. Candès, 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 | K. D. Levin and B. Betancourt | Fast Generation of Exchangeable Sequence of Clusters Data |
| 2022 | Vivak Patel | Stopping criteria for, and strong convergence of, stochastic gradient descent on Bottou-Curtis-Nocedal functions |
| 2022 | Vivak Patel, Mohammad Jahangoshahi, Daniel Adrian Maldonado | Block Adaptive Randomized Linear System Solvers |
| 2022 | Vivak Patel, Shushu Zhang, Bowen Tian | Global Convergence and Stability of Stochastic Gradient Descent |
| 2022 | Nathaniel Pritchard, Vivak Patel | Towards Practical Large-scale Randomized Iterative Least Squares Solversthrough Uncertainty Quantification |
| 2022 | Nathaniel Pritchard, Vivak Patel | Residual Tracking and Stopping for Iterative Random Sketching |
| 2022 | Vivak Patel, Albert Berahas | Gradient descent in the absence of global Lipschitz continuity of the gradients |
| 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 | Alex Hayes, Mark Fredrickson, Keith Levin | Estimating network-mediated causal effects via spectral embeddings |
| 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 García 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 | Jingcheng Xu, Cécile Ané | Identifiability of local and global features of phylogenetic networks from average distances |
| 2023 | Benjamin Teo, Jeffrey P. Rose, Paul Bastide, Cécile Ané | Accounting for within-species variation in continuous trait evolution on a phylogenetic network |
| 2023 | Hanbaek Lyu | Convergence and complexity of block coordinate descent with diminishing radius for nonconvex optimization |
| 2023 | Hanbaek Lyu | Stochastic regularized block majorization-minimization with weakly convex and multi-convex surrogates |
| 2023 | Hanbaek Lyu, Yacoub Kureh, Joshua Vendrow, Mason A. Porter | Learning low-rank latent mesoscale structures in networks |
| 2023 | Hanbaek Lyu, Facundo Memoli, and David Sivakoff | Sampling random graph homomorphisms and applications to network data analysis |
| 2023 | Dohyun Kwon, Hanbaek Lyu | Complexity of block coordinate descent with proximal regularization and applications to Wasserstein CP-dictionary learning |
| 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, Jelena Diakonikolas, and Stephen Wright | 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, Cécile Ané | PhyloCoalSimulations: A simulator for network multispecies coalescent models, including a new extension for the inheritance of gene flow |
| 2023 | Lauren Frankel, Cécile Ané | 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 SJÖGREN'S DISEASE |
| 2023 | García Trillos, C. and García Trillos, N. | On adversarial robustness and the use of Wasserstein ascent-descent dynamics to enforce it |
| 2023 | García Trillos, N. and Jacobs, M. and Kim, J. | On the existence of solutions to adversarial training in multiclass classification |
| 2023 | Carrillo, J.A. and García Trillos, N. and Li, S. and Zhu, Y. | FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization |
| 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 | P Yu, Y Lian, C Zuleger, RJ Albertini, MR Albertini, & MA Newton | Surrogate selection oversamples expanded T cell clonotypes |
| 2023 | Le, Phong V. V., James T. Randerson, Rebecca Willett, Stephen Wright, Padhraic Smyth, Clément 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, Lang Liu, Krishna Pillutla, Yejin Choi, Zaid Harchaoui | Influence Diagnostics under Self-concordance |
| 2023 | Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaid 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. Candès, Aaditya Ramdas, and Ryan Tibshirani | De Finetti’s 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 Başar | 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. |
| 2023 | Ahmet Alacaoglu, Axel Böhm, 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
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| 2023 | Shyam Nuggehalli, Jifan Zhang, Lalit Jain, Robert Nowak
| Direct: Deep active learning under imbalance and label noise
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| 2023 | Liu Yang, Kangwook Lee, Robert Nowak, Dimitris Papailiopoulos
| Looped Transformers are Better at Learning Learning Algorithms
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| 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
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| 2023 | Ronald DeVore, Robert D Nowak, Rahul Parhi, Jonathan W Siegel
| Weighted variation spaces and approximation by shallow ReLU networks
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| 2023 | Joseph Shenouda, Rahul Parhi, Robert D. Nowak | A Continuous Transform for Localized Ridgelets
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| 2023 | Danica Fliss, Willem Marais, Robert D Nowak
| Filtered Iterative Denoising for Linear Inverse Problems
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| 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
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| 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 | Cécile Ané, John Fogg, Elizabeth S. Allman, Hector Baños, John A. Rhodes | Anomalous networks under the multispecies coalescent: theory and prevalence |
| 2024 | John A. Rhodes, Hector Baños, Jingcheng Xu, Cécile Ané | Identifying circular orders for blobs in phylogenetic networks |
| 2024 | Benjamin Teo, Paul Bastide, Cécile Ané | Leveraging graphical model techniques to study evolution on phylogenetic networks |
| 2024 | Michael Maxfield, Jingcheng Xu, Cécile Ané | A dissimilarity measure for semidirected networks |
| 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
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| 2024 | Jeongyeol Kwon, Liu Yang, Robert Nowak, Josiah Hanna
| Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments
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| 2024 | Nasim Soltani, Jifan Zhang, Batool Salehi, Debashri Roy, Robert Nowak, Kaushik Chowdhury
| Learning from the Best: Active Learning for Wireless Communications
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| 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 |
