When Will Gradient Methods Converge to Max-margin Classifier under ReLU Models?

12 June 2018

Papers citing "When Will Gradient Methods Converge to Max-margin Classifier under ReLU Models?"

7 / 7 papers shown

Title
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks Bohan Wang Qi Meng Wei Chen Tie-Yan Liu 22 33 0 11 Dec 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 16 327 0 11 Feb 2020
Sampling Bias in Deep Active Classification: An Empirical Study Ameya Prabhu Charles Dognin M. Singh 11 64 0 20 Sep 2019
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 34 321 0 13 Jun 2019
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models Mor Shpigel Nacson Suriya Gunasekar J. Lee Nathan Srebro Daniel Soudry 17 91 0 17 May 2019
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization G. Wang G. Giannakis Jie Chen MLT 24 131 0 14 Aug 2018
Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate Mor Shpigel Nacson Nathan Srebro Daniel Soudry FedML MLT 19 97 0 05 Jun 2018