Srebro, Nati

46 publications

NeurIPS 2023 Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy Amit Daniely, Nati Srebro, Gal Vardi

NeurIPS 2023 Most Neural Networks Are Almost Learnable Amit Daniely, Nati Srebro, Gal Vardi

NeurIPS 2023 The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro

NeurIPS 2023 Uniform Convergence with Square-Root Lipschitz Loss Lijia Zhou, Zhen Dai, Frederic Koehler, Nati Srebro

NeurIPS 2023 When Is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro

NeurIPS 2022 A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland, Nati Srebro

NeurIPS 2022 Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization Omar Montasser, Steve Hanneke, Nati Srebro

NeurIPS 2022 Exponential Family Model-Based Reinforcement Learning via Score Matching Gene Li, Junbo Li, Anmol Kabra, Nati Srebro, Zhaoran Wang, Zhuoran Yang

NeurIPS 2022 On Margin Maximization in Linear and ReLU Networks Gal Vardi, Ohad Shamir, Nati Srebro

NeurIPS 2022 Pessimism for Offline Linear Contextual Bandits Using $\ell_p$ Confidence Sets Gene Li, Cong Ma, Nati Srebro

NeurIPS 2022 The Sample Complexity of One-Hidden-Layer Neural Networks Gal Vardi, Ohad Shamir, Nati Srebro

NeurIPS 2022 Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization Idan Amir, Roi Livni, Nati Srebro

NeurIPS 2022 Towards Optimal Communication Complexity in Distributed Non-Convex Optimization Kumar Kshitij Patel, Lingxiao Wang, Blake E Woodworth, Brian Bullins, Nati Srebro

NeurIPS 2022 Understanding the Eluder Dimension Gene Li, Pritish Kamath, Dylan J Foster, Nati Srebro

NeurIPS 2020 Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy Edward Moroshko, Blake E Woodworth, Suriya Gunasekar, Jason Lee, Nati Srebro, Daniel Soudry

NeurIPS 2020 Minibatch vs Local SGD for Heterogeneous Distributed Learning Blake E Woodworth, Kumar Kshitij Patel, Nati Srebro

NeurIPS 2020 On Uniform Convergence and Low-Norm Interpolation Learning Lijia Zhou, Danica J. Sutherland, Nati Srebro

NeurIPS 2020 Reducing Adversarially Robust Learning to Non-Robust PAC Learning Omar Montasser, Steve Hanneke, Nati Srebro

NeurIPS 2018 Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization Blake E Woodworth, Jialei Wang, Adam Smith, Brendan McMahan, Nati Srebro

NeurIPS 2018 Implicit Bias of Gradient Descent on Linear Convolutional Networks Suriya Gunasekar, Jason Lee, Daniel Soudry, Nati Srebro

NeurIPS 2018 On Preserving Non-Discrimination When Combining Expert Advice Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nati Srebro

NeurIPS 2018 The Everlasting Database: Statistical Validity at a Fair Price Blake E Woodworth, Vitaly Feldman, Saharon Rosset, Nati Srebro

NeurIPS 2017 Exploring Generalization in Deep Learning Behnam Neyshabur, Srinadh Bhojanapalli, David Mcallester, Nati Srebro

NeurIPS 2017 Implicit Regularization in Matrix Factorization Suriya Gunasekar, Blake E Woodworth, Srinadh Bhojanapalli, Behnam Neyshabur, Nati Srebro

AISTATS 2017 Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-Dimensional Data Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nati Srebro

NeurIPS 2017 Stochastic Approximation for Canonical Correlation Analysis Raman Arora, Teodor Vanislavov Marinov, Poorya Mianjy, Nati Srebro

NeurIPS 2017 The Marginal Value of Adaptive Gradient Methods in Machine Learning Ashia C Wilson, Rebecca Roelofs, Mitchell Stern, Nati Srebro, Benjamin Recht

NeurIPS 2016 Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis Weiran Wang, Jialei Wang, Dan Garber, Dan Garber, Nati Srebro

NeurIPS 2016 Equality of Opportunity in Supervised Learning Moritz Hardt, Eric Price, Ecprice, Nati Srebro

NeurIPS 2016 Global Optimality of Local Search for Low Rank Matrix Recovery Srinadh Bhojanapalli, Behnam Neyshabur, Nati Srebro

NeurIPS 2016 Normalized Spectral mAP Synchronization Yanyao Shen, Qixing Huang, Nati Srebro, Sujay Sanghavi

NeurIPS 2016 Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nati Srebro

NeurIPS 2016 Tight Complexity Bounds for Optimizing Composite Objectives Blake E Woodworth, Nati Srebro

NeurIPS 2015 Path-SGD: Path-Normalized Optimization in Deep Neural Networks Behnam Neyshabur, Ruslan Salakhutdinov, Nati Srebro

ICML 2014 Communication-Efficient Distributed Optimization Using an Approximate Newton-Type Method Ohad Shamir, Nati Srebro, Tong Zhang

NeurIPS 2014 Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz Algorithm Deanna Needell, Rachel Ward, Nati Srebro

NeurIPS 2013 Auditing: Active Learning with Outcome-Dependent Query Costs Sivan Sabato, Anand D Sarwate, Nati Srebro

ICML 2013 Learning Optimally Sparse Support Vector Machines Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro

ICML 2013 Mini-Batch Primal and Dual Methods for SVMs Martin Takac, Avleen Bijral, Peter Richtarik, Nati Srebro

NeurIPS 2013 Stochastic Optimization of PCA with Capped MSG Raman Arora, Andy Cotter, Nati Srebro

NeurIPS 2013 The Power of Asymmetry in Binary Hashing Behnam Neyshabur, Nati Srebro, Ruslan Salakhutdinov, Yury Makarychev, Payman Yadollahpour

NeurIPS 2011 Beating SGD: Learning SVMs in Sublinear Time Elad Hazan, Tomer Koren, Nati Srebro

NeurIPS 2011 Better Mini-Batch Algorithms via Accelerated Gradient Methods Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan

NeurIPS 2011 Learning with the Weighted Trace-Norm Under Arbitrary Sampling Distributions Rina Foygel, Ohad Shamir, Nati Srebro, Ruslan Salakhutdinov

NeurIPS 2011 On the Universality of Online Mirror Descent Nati Srebro, Karthik Sridharan, Ambuj Tewari

ICML 2010 On the Interaction Between Norm and Dimensionality: Multiple Regimes in Learning Percy Liang, Nati Srebro