Recovery Guarantees for One-hidden-layer Neural Networks

10 June 2017

Inderjit S. Dhillon

Papers citing "Recovery Guarantees for One-hidden-layer Neural Networks"

50 / 223 papers shown

Title
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins Dawei Li Tian Ding Ruoyu Sun 29 37 0 28 Dec 2018
Towards a Theoretical Understanding of Hashing-Based Neural Nets Yibo Lin Zhao Song Lin F. Yang 14 5 0 26 Dec 2018
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? Samet Oymak Mahdi Soltanolkotabi ODL 6 176 0 25 Dec 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 9 765 0 12 Nov 2018
A Convergence Theory for Deep Learning via Over-Parameterization Zeyuan Allen-Zhu Yuanzhi Li Zhao Song AI4CE ODL 22 1,447 0 09 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du J. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 44 1,122 0 09 Nov 2018
Learning Two Layer Rectified Neural Networks in Polynomial Time Ainesh Bakshi Rajesh Jayaram David P. Woodruff NoLa 13 69 0 05 Nov 2018
Towards a Zero-One Law for Column Subset Selection Zhao Song David P. Woodruff Peilin Zhong 21 32 0 04 Nov 2018
On the Convergence Rate of Training Recurrent Neural Networks Zeyuan Allen-Zhu Yuanzhi Li Zhao Song 23 191 0 29 Oct 2018
Subgradient Descent Learns Orthogonal Dictionaries Yu Bai Qijia Jiang Ju Sun 20 51 0 25 Oct 2018
Depth with Nonlinearity Creates No Bad Local Minima in ResNets Kenji Kawaguchi Yoshua Bengio ODL 17 64 0 21 Oct 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 26 117 0 17 Oct 2018
Learning Two-layer Neural Networks with Symmetric Inputs Rong Ge Rohith Kuditipudi Zhize Li Xiang Wang OOD MLT 36 57 0 16 Oct 2018
Learning One-hidden-layer Neural Networks under General Input Distributions Weihao Gao Ashok Vardhan Makkuva Sewoong Oh Pramod Viswanath MLT 25 28 0 09 Oct 2018
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks Sanjeev Arora Nadav Cohen Noah Golowich Wei Hu 27 281 0 04 Oct 2018
Efficiently testing local optimality and escaping saddles for ReLU networks Chulhee Yun S. Sra Ali Jadbabaie 30 10 0 28 Sep 2018
On the loss landscape of a class of deep neural networks with no bad local valleys Quynh N. Nguyen Mahesh Chandra Mukkamala Matthias Hein 16 87 0 27 Sep 2018
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview Yuejie Chi Yue M. Lu Yuxin Chen 39 416 0 25 Sep 2018
Stochastic Gradient Descent Learns State Equations with Nonlinear Activations Samet Oymak 16 43 0 09 Sep 2018
Two Dimensional Stochastic Configuration Networks for Image Data Analytics Ming Li Dianhui Wang 14 2 0 06 Sep 2018
On the Decision Boundary of Deep Neural Networks Yu Li Lizhong Ding Xin Gao UQCV 6 35 0 16 Aug 2018
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization G. Wang G. Giannakis Jie Chen MLT 24 131 0 14 Aug 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 34 650 0 03 Aug 2018
Tensor Methods for Additive Index Models under Discordance and Heterogeneity Krishnakumar Balasubramanian Jianqing Fan Zhuoran Yang 19 13 0 17 Jul 2018
Model Reconstruction from Model Explanations S. Milli Ludwig Schmidt Anca Dragan Moritz Hardt FAtt 21 177 0 13 Jul 2018
Learning ReLU Networks via Alternating Minimization Gauri Jagatap C. Hegde 22 11 0 20 Jun 2018
Learning One-hidden-layer ReLU Networks via Gradient Descent Xiao Zhang Yaodong Yu Lingxiao Wang Quanquan Gu MLT 28 134 0 20 Jun 2018
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced S. Du Wei Hu J. Lee MLT 26 236 0 04 Jun 2018
Autoencoders Learn Generative Linear Models THANH VAN NGUYEN Raymond K. W. Wong C. Hegde DRL 11 4 0 02 Jun 2018
Nonlinear Inductive Matrix Completion based on One-layer Neural Networks Kai Zhong Zhao Song Prateek Jain Inderjit S. Dhillon 9 6 0 26 May 2018
A Unified Framework for Training Neural Networks H. Ghauch H. S. Ghadikolaei Carlo Fischione Mikael Skoglund AI4CE 16 0 0 23 May 2018
Adding One Neuron Can Eliminate All Bad Local Minima Shiyu Liang Ruoyu Sun J. Lee R. Srikant 37 89 0 22 May 2018
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network? S. Du Yining Wang Xiyu Zhai Sivaraman Balakrishnan Ruslan Salakhutdinov Aarti Singh SSL 21 57 0 21 May 2018
Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps S. Du Surbhi Goel MLT 30 17 0 20 May 2018
End-to-end Learning of a Convolutional Neural Network via Deep Tensor Decomposition Samet Oymak Mahdi Soltanolkotabi 21 12 0 16 May 2018
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds Santosh Vempala John Wilmes MLT 6 50 0 07 May 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 43 850 0 18 Apr 2018
A Provably Correct Algorithm for Deep Learning that Actually Works Eran Malach Shai Shalev-Shwartz MLT 8 30 0 26 Mar 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du J. Lee 27 267 0 03 Mar 2018
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms Ashok Vardhan Makkuva Sewoong Oh Sreeram Kannan Pramod Viswanath MoE 8 18 0 21 Feb 2018
On the Connection Between Learning Two-Layers Neural Networks and Tensor Decomposition Marco Mondelli Andrea Montanari MLT CML 10 58 0 20 Feb 2018
Understanding the Loss Surface of Neural Networks for Binary Classification Shiyu Liang Ruoyu Sun Yixuan Li R. Srikant 21 87 0 19 Feb 2018
Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy H. Fu Yuejie Chi Yingbin Liang FedML 27 39 0 18 Feb 2018
Nonconvex Matrix Factorization from Rank-One Measurements Yuanxin Li Cong Ma Yuxin Chen Yuejie Chi 25 51 0 17 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 33 116 0 16 Feb 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 39 116 0 13 Feb 2018
Small nonlinearities in activation functions create bad local minima in neural networks Chulhee Yun S. Sra Ali Jadbabaie ODL 20 93 0 10 Feb 2018
Learning One Convolutional Layer with Overlapping Patches Surbhi Goel Adam R. Klivans Raghu Meka MLT 16 80 0 07 Feb 2018
Learning Compact Neural Networks with Regularization Samet Oymak MLT 41 39 0 05 Feb 2018
The Multilinear Structure of ReLU Networks T. Laurent J. V. Brecht 25 51 0 29 Dec 2017