Blake E. Woodworth

50 papers A* 20A 2Misc 1Journal 25Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Lower bounds for non-convex stochastic optimization. Math. Program. Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Nathan Srebro, Blake E. Woodworth
2023	A*	`conf`	Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy. ICML Blake E. Woodworth, Konstantin Mishchenko, Francis R. Bach
2023	J	`jnl`	Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy. CoRR Blake E. Woodworth, Konstantin Mishchenko, Francis R. Bach
2022	A*	`conf`	Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. NeurIPS Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E. Woodworth
2022	J	`jnl`	Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. CoRR Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E. Woodworth
2022	A*	`conf`	Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. COLT Blake E. Woodworth, Francis R. Bach, Alessandro Rudi
2022	J	`jnl`	Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. CoRR Blake E. Woodworth, Francis R. Bach, Alessandro Rudi
2022	A*	`conf`	The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication (Extended Abstract). IJCAI Blake E. Woodworth, Brian Bullins, Ohad Shamir, Nathan Srebro
2022	A*	`conf`	Towards Optimal Communication Complexity in Distributed Non-Convex Optimization. NeurIPS Kumar Kshitij Patel, Lingxiao Wang, Blake E. Woodworth, Brian Bullins, Nati Srebro
2021	J	`jnl`	A Field Guide to Federated Optimization. CoRR Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
2021	A*	`conf`	A Stochastic Newton Algorithm for Distributed Convex Optimization. NeurIPS Brian Bullins, Kumar Kshitij Patel, Ohad Shamir, Nathan Srebro, Blake E. Woodworth
2021	J	`jnl`	A Stochastic Newton Algorithm for Distributed Convex Optimization. CoRR Brian Bullins, Kumar Kshitij Patel, Ohad Shamir, Nathan Srebro, Blake E. Woodworth
2021	A*	`conf`	An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning. NeurIPS Blake E. Woodworth, Nathan Srebro
2021	J	`jnl`	An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning. CoRR Blake E. Woodworth, Nathan Srebro
2021	A	`conf`	Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent. AISTATS Suriya Gunasekar, Blake E. Woodworth, Nathan Srebro
2021	A*	`conf`	On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent. ICML Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E. Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry
2021	J	`jnl`	On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent. CoRR Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E. Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry
2021	A*	`conf`	The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication. COLT Blake E. Woodworth, Brian Bullins, Ohad Shamir, Nathan Srebro
2021	J	`jnl`	The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication. CoRR Blake E. Woodworth, Brian Bullins, Ohad Shamir, Nathan Srebro
2021	J	`jnl`	The Minimax Complexity of Distributed Optimization. CoRR Blake E. Woodworth
2020	A	`conf`	Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis. AISTATS Ryan Rogers, Aaron Roth, Adam D. Smith, Nathan Srebro, Om Thakkar, Blake E. Woodworth
2020	A*	`conf`	Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy. NeurIPS Edward Moroshko, Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Nati Srebro, Daniel Soudry
2020	J	`jnl`	Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy. CoRR Edward Moroshko, Suriya Gunasekar, Blake E. Woodworth, Jason D. Lee, Nathan Srebro, Daniel Soudry
2020	A*	`conf`	Is Local SGD Better than Minibatch SGD? ICML Blake E. Woodworth, Kumar Kshitij Patel, Sebastian U. Stich, Zhen Dai, Brian Bullins, H. Brendan McMahan, Ohad Shamir, Nathan Srebro
2020	J	`jnl`	Is Local SGD Better than Minibatch SGD? CoRR Blake E. Woodworth, Kumar Kshitij Patel, Sebastian U. Stich, Zhen Dai, Brian Bullins, H. Brendan McMahan, Ohad Shamir, Nathan Srebro
2020	A*	`conf`	Kernel and Rich Regimes in Overparametrized Models. COLT Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro
2020	J	`jnl`	Kernel and Rich Regimes in Overparametrized Models. CoRR Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro
2020	A*	`conf`	Minibatch vs Local SGD for Heterogeneous Distributed Learning. NeurIPS Blake E. Woodworth, Kumar Kshitij Patel, Nati Srebro
2020	J	`jnl`	Minibatch vs Local SGD for Heterogeneous Distributed Learning. CoRR Blake E. Woodworth, Kumar Kshitij Patel, Nathan Srebro
2020	J	`jnl`	Mirrorless Mirror Descent: A More Natural Discretization of Riemannian Gradient Flow. CoRR Suriya Gunasekar, Blake E. Woodworth, Nathan Srebro
2020	A*	`conf`	The Gradient Complexity of Linear Regression. COLT Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth
2019	J	`jnl`	Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis. CoRR Ryan Rogers, Aaron Roth, Adam D. Smith, Nathan Srebro, Om Thakkar, Blake E. Woodworth
2019	J	`jnl`	Lower Bounds for Non-Convex Stochastic Optimization. CoRR Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Nathan Srebro, Blake E. Woodworth
2019	A*	`conf`	Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory. COLT Blake E. Woodworth, Nathan Srebro
2019	J	`jnl`	Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory. CoRR Blake E. Woodworth, Nathan Srebro
2019	A*	`conf`	The Complexity of Making the Gradient Small in Stochastic Convex Optimization. COLT Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake E. Woodworth
2019	J	`jnl`	The Complexity of Making the Gradient Small in Stochastic Convex Optimization. CoRR Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake E. Woodworth
2019	J	`jnl`	The gradient complexity of linear regression. CoRR Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth
2019	A*	`conf`	Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. ICML Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You
2018	A*	`conf`	Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization. NeurIPS Blake E. Woodworth, Jialei Wang, Adam D. Smith, Brendan McMahan, Nati Srebro
2018	J	`jnl`	Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization. CoRR Blake E. Woodworth, Jialei Wang, Brendan McMahan, Nathan Srebro
2018	Misc	`conf`	Implicit Regularization in Matrix Factorization. ITA Suriya Gunasekar, Blake E. Woodworth, Srinadh Bhojanapalli, Behnam Neyshabur, Nathan Srebro
2018	A*	`conf`	The Everlasting Database: Statistical Validity at a Fair Price. NeurIPS Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nati Srebro
2018	J	`jnl`	The Everlasting Database: Statistical Validity at a Fair Price. CoRR Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nathan Srebro
2018	J	`jnl`	Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. CoRR Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You
2017	—	`conf`	Implicit Regularization in Matrix Factorization. NIPS Suriya Gunasekar, Blake E. Woodworth, Srinadh Bhojanapalli, Behnam Neyshabur, Nati Srebro
2017	J	`jnl`	Implicit Regularization in Matrix Factorization. CoRR Suriya Gunasekar, Blake E. Woodworth, Srinadh Bhojanapalli, Behnam Neyshabur, Nathan Srebro
2017	A*	`conf`	Learning Non-Discriminatory Predictors. COLT Blake E. Woodworth, Suriya Gunasekar, Mesrob I. Ohannessian, Nathan Srebro
2017	J	`jnl`	Learning Non-Discriminatory Predictors. CoRR Blake E. Woodworth, Suriya Gunasekar, Mesrob I. Ohannessian, Nathan Srebro
2016	—	`conf`	Tight Complexity Bounds for Optimizing Composite Objectives. NIPS Blake E. Woodworth, Nati Srebro