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Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank

27 November 2020

Papers citing "Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank"

21 / 21 papers shown

Title
How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective Siyi Lin Chongming Gao Jiawei Chen Sheng Zhou Binbin Hu Yan Feng Chun-Yen Chen Can Wang 128 8 0 18 Apr 2024
Implicit Regularization in Deep Learning May Not Be Explainable by Norms Noam Razin Nadav Cohen 66 156 0 13 May 2020
Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers B. Bah Holger Rauhut Ulrich Terstiege Michael Westdickenberg MLT 34 66 0 12 Oct 2019
The Implicit Bias of Depth: How Incremental Learning Drives Generalization Daniel Gissin Shai Shalev-Shwartz Amit Daniely AI4CE 90 81 0 26 Sep 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 85 509 0 31 May 2019
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks Gauthier Gidel Francis R. Bach Simon Lacoste-Julien AI4CE 70 155 0 30 Apr 2019
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks Reinhard Heckel Paul Hand 90 287 0 02 Oct 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 271 3,213 0 20 Jun 2018
Implicit regularization and solution uniqueness in over-parameterized matrix sensing Kelly Geyer Anastasios Kyrillidis A. Kalev 106 4 0 06 Jun 2018
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced S. Du Wei Hu Jason D. Lee MLT 133 243 0 04 Jun 2018
Implicit Bias of Gradient Descent on Linear Convolutional Networks Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro MDE 124 413 0 01 Jun 2018
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization Sanjeev Arora Nadav Cohen Elad Hazan 102 488 0 19 Feb 2018
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks Peter L. Bartlett D. Helmbold Philip M. Long 92 117 0 16 Feb 2018
Deep Image Prior Dmitry Ulyanov Andrea Vedaldi Victor Lempitsky SupR 125 3,161 0 29 Nov 2017
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 161 921 0 27 Oct 2017
Implicit Regularization in Matrix Factorization Suriya Gunasekar Blake E. Woodworth Srinadh Bhojanapalli Behnam Neyshabur Nathan Srebro 79 493 0 25 May 2017
Geometry of Optimization and Implicit Regularization in Deep Learning Behnam Neyshabur Ryota Tomioka Ruslan Salakhutdinov Nathan Srebro AI4CE 67 133 0 08 May 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 345 4,636 0 10 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 429 2,945 0 15 Sep 2016
Deep Learning without Poor Local Minima Kenji Kawaguchi ODL 224 925 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 94 660 0 20 Dec 2014