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ppointer
2022-07-19T16:25:17-05:00
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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
Alacaoglu, A., Cevher, V., and Wright, S. J.
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
Benjamin Teo, Jeffrey P. Rose, Paul Bastide, Ccile An
Accounting for intraspecific variation in continuous trait evolution on a reticulate phylogeny
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
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
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
Alacaoglu, A., Lyu, H.
Convergence and Complexity of Stochastic Subgradient Methods with Dependent Data for Nonconvex Optimization
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
Lijun Ding, Dmitriy Drusvyatskiy, Maryam Fazel
Flat minima generalize for low-rank matrix recovery
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
Generalized permutation tests
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
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, Jrme 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
Bhm, 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
Jingcheng Xu, Ccile An
Identifiability of local and global features of phylogenetic networks from average distances
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
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
Yuchen Zeng, Hongxu Chen, Kangwook Lee
Improving Fairness via Federated Learning
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 Amndola, 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
2020
Haotian Jiang, Tarun Kathuria, Yin Tat Lee, Swati Padmanabhan, Zhao Song
A Faster Interior Point Method for Semidefinite Programming
2020
O'Neill, M. and Wright, S. J.
A Line-search descent algorithm for strict saddle functions with complexity guarantees
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
Sbastien 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 Tnczos, 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 Elis, 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
Error analysis of an asymptotic preserving dynamical low-rank integrator for the multi-scale radiative transfer equation
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 _-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 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
Sbastien 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
Grbzbalaban, 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
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
2018
Yuanzhi Li, Yingyu Liang
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals
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
Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees
Lang Liu, Soumik Pal, Zaid Harchaoui
Entropy Regularized Optimal Transport Independence Criterion
Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaid Harchaoui
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates
Hanbaek Lyu, Christopher Strohmeier, Deanna Needell
Online nonnegative tensor factorization and CP-Dictionary Learning for Markovian data
Hanbaek Lyu
Convergence and complexity of block coordinate descent with diminishing radius for nonconvex optimization
Hanbaek Lyu
Stochastic regularized block majorization-minimization with weakly convex and multi-convex surrogates
Joowon Lee, Hanbaek Lyu, and Weixin Yao
Supervised Dictionary Learning with Auxiliary Covariates
Hardeep Bassi, Richard Yim, Rohith Kodukula, Joshua Vendrow, Cherlin Zhu, Hanbaek Lyu
Learning to predict synchronization of coupled oscillators on heterogeneous graphs
Hanbaek Lyu, Yacoub Kureh, Joshua Vendrow*, Mason A. Porter
Learning low-rank latent mesoscale structures in networks
Hanbaek Lyu, Facundo Memoli, and David Sivakoff
Sampling random graph homomorphisms and applications to network data analysis
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