Deep Learning without Poor Local Minima

23 May 2016

Papers citing "Deep Learning without Poor Local Minima"

50 / 205 papers shown

Title
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 39 6,119 0 22 Oct 2019
Active Learning for Graph Neural Networks via Node Feature Propagation Yuexin Wu Yichong Xu Aarti Singh Yiming Yang A. Dubrawski GNN AI4CE 48 63 0 16 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
Solving Continual Combinatorial Selection via Deep Reinforcement Learning Hyungseok Song Hyeryung Jang H. Tran Se-eun Yoon Kyunghwan Son Donggyu Yun Hyoju Chung Yung Yi 18 10 0 09 Sep 2019
Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization Stefan Vlaski Ali H. Sayed ODL 29 21 0 19 Aug 2019
Behaviour Suite for Reinforcement Learning Ian Osband Yotam Doron Matteo Hessel John Aslanides Eren Sezener ... Satinder Singh Benjamin Van Roy R. Sutton David Silver H. V. Hasselt OffRL 32 178 0 09 Aug 2019
Post-synaptic potential regularization has potential Enzo Tartaglione Daniele Perlo Marco Grangetto BDL AAML 27 6 0 19 Jul 2019
SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems Songtao Lu Meisam Razaviyayn Bo Yang Kejun Huang Mingyi Hong 27 11 0 09 Jul 2019
Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape Johanni Brea Berfin Simsek Bernd Illing W. Gerstner 23 55 0 05 Jul 2019
Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks M. Fornasier T. Klock Michael Rauchensteiner 24 18 0 30 Jun 2019
Empirical study of extreme overfitting points of neural networks D. Merkulov Ivan Oseledets 3DPC 24 7 0 14 Jun 2019
Deep Network Approximation Characterized by Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 23 182 0 13 Jun 2019
Interpretable Few-Shot Learning via Linear Distillation Arip Asadulaev Igor Kuznetsov Andrey Filchenkov FedML FAtt 11 1 0 13 Jun 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 37 186 0 05 Jun 2019
On the Expressive Power of Deep Polynomial Neural Networks Joe Kileel Matthew Trager Joan Bruna 27 82 0 29 May 2019
Why gradient clipping accelerates training: A theoretical justification for adaptivity J.N. Zhang Tianxing He S. Sra Ali Jadbabaie 30 445 0 28 May 2019
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 24 183 0 24 May 2019
Fine-grained Optimization of Deep Neural Networks Mete Ozay ODL 16 1 0 22 May 2019
Orthogonal Deep Neural Networks Kui Jia Shuai Li Yuxin Wen Tongliang Liu Dacheng Tao 36 132 0 15 May 2019
Every Local Minimum Value is the Global Minimum Value of Induced Model in Non-convex Machine Learning Kenji Kawaguchi Jiaoyang Huang L. Kaelbling AAML 24 18 0 07 Apr 2019
Nonlinear Approximation via Compositions Zuowei Shen Haizhao Yang Shijun Zhang 26 92 0 26 Feb 2019
Supervised Deep Neural Networks (DNNs) for Pricing/Calibration of Vanilla/Exotic Options Under Various Different Processes Ali Hirsa T. Karatas Amir Oskoui 19 26 0 15 Feb 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 55 961 0 24 Jan 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks S. Du Wei Hu 23 94 0 24 Jan 2019
Understanding Geometry of Encoder-Decoder CNNs J. C. Ye Woon Kyoung Sung 3DV AI4CE 14 72 0 22 Jan 2019
A Deterministic Gradient-Based Approach to Avoid Saddle Points L. Kreusser Stanley J. Osher Bao Wang ODL 32 3 0 21 Jan 2019
Overfitting Mechanism and Avoidance in Deep Neural Networks Shaeke Salman Xiuwen Liu 11 139 0 19 Jan 2019
The Oracle of DLphi Dominik Alfke W. Baines J. Blechschmidt Mauricio J. del Razo Sarmina Amnon Drory ... L. Thesing Philipp Trunschke Johannes von Lindheim David Weber Melanie Weber 39 0 0 17 Jan 2019
Visualising Basins of Attraction for the Cross-Entropy and the Squared Error Neural Network Loss Functions Anna Sergeevna Bosman A. Engelbrecht Mardé Helbig 16 76 0 08 Jan 2019
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks Henning Petzka C. Sminchisescu 29 9 0 16 Dec 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 33 446 0 21 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 32 765 0 12 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du J. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 44 1,125 0 09 Nov 2018
A Closer Look at Deep Policy Gradients Andrew Ilyas Logan Engstrom Shibani Santurkar Dimitris Tsipras Firdaus Janoos Larry Rudolph Aleksander Madry 30 50 0 06 Nov 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 28 117 0 17 Oct 2018
Stein Neural Sampler Tianyang Hu Zixiang Chen Hanxi Sun Jincheng Bai Mao Ye Guang Cheng SyDa GAN 22 34 0 08 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
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 56 1,252 0 04 Oct 2018
Interpreting Adversarial Robustness: A View from Decision Surface in Input Space Fuxun Yu Chenchen Liu Yanzhi Wang Liang Zhao Xiang Chen AAML OOD 36 27 0 29 Sep 2018
A theoretical framework for deep locally connected ReLU network Yuandong Tian PINN 25 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
Exponential Convergence Time of Gradient Descent for One-Dimensional Deep Linear Neural Networks Ohad Shamir 35 45 0 23 Sep 2018
Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System Jiaxi Tang Ke Wang 27 182 0 19 Sep 2018
Towards Understanding Regularization in Batch Normalization Ping Luo Xinjiang Wang Wenqi Shao Zhanglin Peng MLT AI4CE 23 179 0 04 Sep 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
ResNet with one-neuron hidden layers is a Universal Approximator Hongzhou Lin Stefanie Jegelka 43 227 0 28 Jun 2018
On the Implicit Bias of Dropout Poorya Mianjy R. Arora René Vidal 27 66 0 26 Jun 2018
Learning One-hidden-layer ReLU Networks via Gradient Descent Xiao Zhang Yaodong Yu Lingxiao Wang Quanquan Gu MLT 30 134 0 20 Jun 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 32 97 0 14 Jun 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 279 1,944 0 09 Jun 2018