Implicit Regularization in Matrix Factorization

25 May 2017

Srinadh Bhojanapalli

Papers citing "Implicit Regularization in Matrix Factorization"

33 / 133 papers shown

Title
Shape Matters: Understanding the Implicit Bias of the Noise Covariance Jeff Z. HaoChen Colin Wei Jason D. Lee Tengyu Ma 32 94 0 15 Jun 2020
To Each Optimizer a Norm, To Each Norm its Generalization Sharan Vaswani Reza Babanezhad Jose Gallego Aaron Mishkin Simon Lacoste-Julien Nicolas Le Roux 26 8 0 11 Jun 2020
Hadamard Wirtinger Flow for Sparse Phase Retrieval Fan Wu Patrick Rebeschini 13 18 0 01 Jun 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms Noam Razin Nadav Cohen 24 155 0 13 May 2020
Orthogonal Over-Parameterized Training Weiyang Liu Rongmei Lin Zhen Liu James M. Rehg Liam Paull Li Xiong Le Song Adrian Weller 32 41 0 09 Apr 2020
Dropout: Explicit Forms and Capacity Control R. Arora Peter L. Bartlett Poorya Mianjy Nathan Srebro 64 37 0 06 Mar 2020
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 27 77 0 10 Dec 2019
Towards Understanding the Spectral Bias of Deep Learning Yuan Cao Zhiying Fang Yue Wu Ding-Xuan Zhou Quanquan Gu 41 215 0 03 Dec 2019
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery Jicong Fan Lijun Ding Yudong Chen Madeleine Udell 20 70 0 13 Nov 2019
Neural Similarity Learning Weiyang Liu Zhen Liu James M. Rehg Le Song 27 29 0 28 Oct 2019
The Implicit Regularization of Ordinary Least Squares Ensembles Daniel LeJeune Hamid Javadi Richard G. Baraniuk 18 43 0 10 Oct 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 38 85 0 09 Oct 2019
Bregman Proximal Framework for Deep Linear Neural Networks Mahesh Chandra Mukkamala Felix Westerkamp Emanuel Laude Daniel Cremers Peter Ochs 21 7 0 08 Oct 2019
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks Yu Bai Jason D. Lee 24 116 0 03 Oct 2019
Overparameterized Neural Networks Implement Associative Memory Adityanarayanan Radhakrishnan M. Belkin Caroline Uhler BDL 35 71 0 26 Sep 2019
The Implicit Bias of Depth: How Incremental Learning Drives Generalization Daniel Gissin Shai Shalev-Shwartz Amit Daniely AI4CE 14 78 0 26 Sep 2019
Kernel and Rich Regimes in Overparametrized Models Blake E. Woodworth Suriya Gunasekar Pedro H. P. Savarese E. Moroshko Itay Golan Jason D. Lee Daniel Soudry Nathan Srebro 30 353 0 13 Jun 2019
The Implicit Bias of AdaGrad on Separable Data Qian Qian Xiaoyuan Qian 37 23 0 09 Jun 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 38 493 0 31 May 2019
Generalization bounds for deep convolutional neural networks Philip M. Long Hanie Sedghi MLT 42 90 0 29 May 2019
SGD on Neural Networks Learns Functions of Increasing Complexity Preetum Nakkiran Gal Kaplun Dimitris Kalimeris Tristan Yang Benjamin L. Edelman Fred Zhang Boaz Barak MLT 28 236 0 28 May 2019
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models Mor Shpigel Nacson Suriya Gunasekar Jason D. Lee Nathan Srebro Daniel Soudry 33 92 0 17 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 25 109 0 09 May 2019
One-Pass Incomplete Multi-view Clustering Menglei Hu Songcan Chen 6 129 0 02 Mar 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 60 1,614 0 28 Dec 2018
Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications Deren Lei Zichen Sun Yijun Xiao William Yang Wang 35 14 0 01 Nov 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei Jason D. Lee Qiang Liu Tengyu Ma 28 245 0 12 Oct 2018
When Will Gradient Methods Converge to Max-margin Classifier under ReLU Models? Tengyu Xu Yi Zhou Kaiyi Ji Yingbin Liang 31 19 0 12 Jun 2018
Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization Navid Azizan B. Hassibi 24 61 0 04 Jun 2018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport Lénaïc Chizat Francis R. Bach OT 65 726 0 24 May 2018
Characterizing Implicit Bias in Terms of Optimization Geometry Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro AI4CE 46 399 0 22 Feb 2018
Fix your classifier: the marginal value of training the last weight layer Elad Hoffer Itay Hubara Daniel Soudry 35 101 0 14 Jan 2018
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 310 2,896 0 15 Sep 2016