Theoretical insights into the optimization landscape of over-parameterized shallow neural networks

16 July 2017

Papers citing "Theoretical insights into the optimization landscape of over-parameterized shallow neural networks"

31 / 81 papers shown

Title
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 22 146 0 20 May 2020
Symmetry & critical points for a model shallow neural network Yossi Arjevani M. Field 26 13 0 23 Mar 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 30 300 0 08 Jan 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 25 19 0 31 Dec 2019
Convergence and sample complexity of gradient methods for the model-free linear quadratic regulator problem Hesameddin Mohammadi A. Zare Mahdi Soltanolkotabi M. Jovanović 30 121 0 26 Dec 2019
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators Reinhard Heckel Mahdi Soltanolkotabi DiffM 27 81 0 31 Oct 2019
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks Yu Bai J. Lee 11 116 0 03 Oct 2019
Towards Scalable Koopman Operator Learning: Convergence Rates and A Distributed Learning Algorithm Zhiyuan Liu Guohui Ding Lijun Chen Enoch Yeung 12 3 0 30 Sep 2019
Greedy Shallow Networks: An Approach for Constructing and Training Neural Networks Anton Dereventsov Armenak Petrosyan Clayton Webster 11 9 0 24 May 2019
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 16 183 0 24 May 2019
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks Mingchen Li Mahdi Soltanolkotabi Samet Oymak NoLa 26 350 0 27 Mar 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 20 961 0 24 Jan 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks S. Du Wei Hu 11 93 0 24 Jan 2019
Analysis of a Two-Layer Neural Network via Displacement Convexity Adel Javanmard Marco Mondelli Andrea Montanari MLT 32 57 0 05 Jan 2019
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du J. Lee Haochuan Li Liwei Wang M. Tomizuka ODL 13 1,120 0 09 Nov 2018
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani Francis R. Bach Mark W. Schmidt 17 296 0 16 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei J. Lee Qiang Liu Tengyu Ma 16 243 0 12 Oct 2018
Interpretable Convolutional Neural Networks via Feedforward Design C.-C. Jay Kuo Min Zhang Siyang Li Jiali Duan Yueru Chen 17 155 0 05 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 8 1,251 0 04 Oct 2018
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization G. Wang G. Giannakis Jie Chen MLT 22 131 0 14 Aug 2018
Learning One-hidden-layer ReLU Networks via Gradient Descent Xiao Zhang Yaodong Yu Lingxiao Wang Quanquan Gu MLT 21 134 0 20 Jun 2018
Data augmentation instead of explicit regularization Alex Hernández-García Peter König 30 141 0 11 Jun 2018
Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization Navid Azizan B. Hassibi 8 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 9 723 0 24 May 2018
End-to-end Learning of a Convolutional Neural Network via Deep Tensor Decomposition Samet Oymak Mahdi Soltanolkotabi 11 12 0 16 May 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 20 850 0 18 Apr 2018
Visualizing the Loss Landscape of Neural Nets Hao Li Zheng Xu Gavin Taylor Christoph Studer Tom Goldstein 45 1,842 0 28 Dec 2017
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks Itay Safran Ohad Shamir 16 261 0 24 Dec 2017
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data Alon Brutzkus Amir Globerson Eran Malach Shai Shalev-Shwartz MLT 26 276 0 27 Oct 2017
Benefits of depth in neural networks Matus Telgarsky 125 602 0 14 Feb 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 175 1,185 0 30 Nov 2014