Blake Woodworth
Title
Cited by
Cited by
Year
Implicit regularization in matrix factorization
S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro
Advances in Neural Information Processing Systems, 6151-6159, 2017
1412017
Learning non-discriminatory predictors
B Woodworth, S Gunasekar, MI Ohannessian, N Srebro
arXiv preprint arXiv:1702.06081, 2017
1392017
Tight complexity bounds for optimizing composite objectives
BE Woodworth, N Srebro
Advances in neural information processing systems, 3639-3647, 2016
1242016
Graph oracle models, lower bounds, and gaps for parallel stochastic optimization
BE Woodworth, J Wang, A Smith, B McMahan, N Srebro
Advances in neural information processing systems, 8496-8506, 2018
482018
Kernel and rich regimes in overparametrized models
B Woodworth, S Gunasekar, JD Lee, E Moroshko, P Savarese, I Golan, ...
arXiv preprint arXiv:2002.09277, 2020
35*2020
Lower bounds for non-convex stochastic optimization
Y Arjevani, Y Carmon, JC Duchi, DJ Foster, N Srebro, B Woodworth
arXiv preprint arXiv:1912.02365, 2019
332019
Training well-generalizing classifiers for fairness metrics and other data-dependent constraints
A Cotter, M Gupta, H Jiang, N Srebro, K Sridharan, S Wang, B Woodworth, ...
International Conference on Machine Learning, 1397-1405, 2019
322019
The complexity of making the gradient small in stochastic convex optimization
DJ Foster, A Sekhari, O Shamir, N Srebro, K Sridharan, B Woodworth
arXiv preprint arXiv:1902.04686, 2019
162019
Is Local SGD Better than Minibatch SGD?
B Woodworth, KK Patel, SU Stich, Z Dai, B Bullins, HB McMahan, ...
arXiv preprint arXiv:2002.07839, 2020
142020
Lower bound for randomized first order convex optimization
B Woodworth, N Srebro
arXiv preprint arXiv:1709.03594, 2017
142017
Guaranteed validity for empirical approaches to adaptive data analysis
R Rogers, A Roth, A Smith, N Srebro, O Thakkar, B Woodworth
International Conference on Artificial Intelligence and Statistics, 2830-2840, 2020
32020
Mirrorless Mirror Descent: A More Natural Discretization of Riemannian Gradient Flow
S Gunasekar, B Woodworth, N Srebro
arXiv preprint arXiv:2004.01025, 2020
32020
Implicit bias in deep linear classification: Initialization scale vs training accuracy
E Moroshko, S Gunasekar, B Woodworth, JD Lee, N Srebro, D Soudry
arXiv preprint arXiv:2007.06738, 2020
22020
Minibatch vs Local SGD for Heterogeneous Distributed Learning
B Woodworth, KK Patel, N Srebro
arXiv preprint arXiv:2006.04735, 2020
22020
The gradient complexity of linear regression
M Braverman, E Hazan, M Simchowitz, B Woodworth
Conference on Learning Theory, 627-647, 2020
12020
Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory
B Woodworth, N Srebro
arXiv preprint arXiv:1907.00762, 2019
12019
Training Fairness-Constrained Classifiers to Generalize
A Cotter, M Gupta, H Jiang, N Srebro, K Sridharan, S Wang, B Woodworth, ...
FATML, 2018
12018
The everlasting database: Statistical validity at a fair price
BE Woodworth, V Feldman, S Rosset, N Srebro
Advances in Neural Information Processing Systems, 6531-6540, 2018
12018
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