Shahar Azulay

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All published works

Action	Title	Year	Authors
+	On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent	2021	Shahar Azulay Edward Moroshko Mor Shpigel Nacson Blake Woodworth Nathan Srebro Amir Globerson Daniel Soudry
+	Holdout SGD: Byzantine Tolerant Federated Learning	2020	Shahar Azulay Lior Raz Amir Globerson Tomer Koren Yehuda Afek

Common Coauthors

Coauthor	Papers Together
Amir Globerson	2
Blake Woodworth	1
Lior Raz	1
Daniel Soudry	1
Mor Shpigel Nacson	1
Tomer Koren	1
Nathan Srebro	1
Edward Moroshko	1
Yehuda Afek	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Neural Tangent Kernel: Convergence and Generalization in Neural Networks	2018	Arthur Paul Jacot Franck Gabriel Clément Hongler	2
+	Parallelized Stochastic Gradient Descent	2010	Martin Zinkevich Markus Weimer Lihong Li Alex Smola	1
+ PDF Chat	Introduction to Online Convex Optimization	2016	Elad Hazan	1
+	A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks	2018	Sanjeev Arora Nadav Cohen Noah Golowich Wei Hu	1
+	Implicit Regularization in Matrix Factorization	2017	Suriya Gunasekar Blake Woodworth Srinadh Bhojanapalli Behnam Neyshabur Nati Srebro	1
+	A Little Is Enough: Circumventing Defenses For Distributed Learning	2019	Moran Baruch Gilad Baruch Yoav Goldberg	1
+	On Lazy Training in Differentiable Programming	2018	Lénaïc Chizat Edouard Oyallon Francis Bach	1
+	Lexicographic and depth-sensitive margins in homogeneous and non-homogeneous deep models	2019	Mor Shpigel Nacson Suriya Gunasekar Jason D. Lee Nathan Srebro Daniel Soudry	1
+	Characterizing Implicit Bias in Terms of Optimization Geometry	2018	Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro	1
+	Implicit Bias of Gradient Descent on Linear Convolutional Networks	2018	Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro	1
+	Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations	2017	Yuanzhi Li Tengyu Ma Hongyang Zhang	1
+	Matrix Completion has No Spurious Local Minimum	2016	Rong Ge Jason D. Lee Tengyu Ma	1
+	Gradient Descent Provably Optimizes Over-parameterized Neural Networks	2018	Simon S. Du Xiyu Zhai Barnabás Póczos Aarti Singh	1
+	Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced	2018	Simon S. Du Wei Hu Jason D. Lee	1
+	Byzantine Stochastic Gradient Descent	2018	Dan Alistarh Zeyuan Allen-Zhu Jerry Li	1
+	Implicit Regularization for Optimal Sparse Recovery	2019	Tomas Vaškevičius Varun Kanade Patrick Rebeschini	1
+	Mirrorless Mirror Descent: A More Natural Discretization of Riemannian Gradient Flow.	2020	Suriya Gunasekar Blake Woodworth Nathan Srebro	1
+	The Elements of Statistical Learning: Data Mining, Inference, and Prediction 2nd Edition	2020	Trevor Hastie Robert Tibshirani Jerome H. Friedman	1
+	Implicit Regularization in Deep Learning May Not Be Explainable by Norms	2020	Noam Razin Nadav Cohen	1
+	Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy	2020	Edward Moroshko Blake Woodworth Suriya Gunasekar Jason D. Lee Nati Srebro Daniel Soudry	1
+	Implicit Regularization in ReLU Networks with the Square Loss	2020	Gal Vardi Ohad Shamir	1
+	Distributed Robust Learning	2014	Jiashi Feng Huan Xu Shie Mannor	1
+	A unifying view on implicit bias in training linear neural networks	2021	Chulhee Yun Shankar Krishnan Hossein Mobahi	1