Convergence of Gradient Descent on Separable Data

5 March 2018

Papers citing "Convergence of Gradient Descent on Separable Data"

22 / 22 papers shown

Title
Embedding principle of homogeneous neural network for classification problem Jiahan Zhang Yaoyu Zhang Yaoyu Zhang 27 0 0 18 May 2025
How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias Ruiquan Huang Yingbin Liang Jing Yang 78 0 0 02 May 2025
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes Ruiqi Zhang Jingfeng Wu Licong Lin Peter L. Bartlett 43 0 0 05 Apr 2025
Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations Yize Zhao Tina Behnia V. Vakilian Christos Thrampoulidis 110 10 0 20 Feb 2025
Scalable Model Merging with Progressive Layer-wise Distillation Jing Xu Jiazheng Li J.N. Zhang MoMe FedML 186 2 0 18 Feb 2025
The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks Sholom Schechtman Nicolas Schreuder 362 0 0 08 Feb 2025
Implicit Bias and Fast Convergence Rates for Self-attention Bhavya Vasudeva Puneesh Deora Christos Thrampoulidis 44 18 0 08 Feb 2024
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study Assaf Dauber M. Feder Tomer Koren Roi Livni 29 24 0 13 Mar 2020
Gradient descent aligns the layers of deep linear networks Ziwei Ji Matus Telgarsky 91 250 0 04 Oct 2018
When Will Gradient Methods Converge to Max-margin Classifier under ReLU Models? Tengyu Xu Yi Zhou Kaiyi Ji Yingbin Liang 44 19 0 12 Jun 2018
Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate Mor Shpigel Nacson Nathan Srebro Daniel Soudry FedML MLT 51 100 0 05 Jun 2018
Implicit Bias of Gradient Descent on Linear Convolutional Networks Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro MDE 45 408 0 01 Jun 2018
Risk and parameter convergence of logistic regression Ziwei Ji Matus Telgarsky 28 129 0 20 Mar 2018
Characterizing Implicit Bias in Terms of Optimization Geometry Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro AI4CE 57 404 0 22 Feb 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 60 908 0 27 Oct 2017
Train longer, generalize better: closing the generalization gap in large batch training of neural networks Elad Hoffer Itay Hubara Daniel Soudry ODL 134 798 0 24 May 2017
The Power of Normalization: Faster Evasion of Saddle Points Kfir Y. Levy 49 108 0 15 Nov 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 245 4,612 0 10 Nov 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 231 7,951 0 23 May 2016
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning Behnam Neyshabur Ryota Tomioka Nathan Srebro AI4CE 55 655 0 20 Dec 2014
Margins, Shrinkage, and Boosting Matus Telgarsky 44 73 0 18 Mar 2013
Sublinear Optimization for Machine Learning K. Clarkson Elad Hazan David P. Woodruff 50 138 0 21 Oct 2010