A Differential Topological View of Challenges in Learning with Feedforward Neural Networks

26 November 2018

Papers citing "A Differential Topological View of Challenges in Learning with Feedforward Neural Networks"

19 / 19 papers shown

Title
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization Daniel Jakubovitz Raja Giryes AAML 39 210 0 23 Mar 2018
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions Quynh N. Nguyen Mahesh Chandra Mukkamala Matthias Hein MLT 56 54 0 28 Feb 2018
i-RevNet: Deep Invertible Networks J. Jacobsen A. Smeulders Edouard Oyallon 75 333 0 20 Feb 2018
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization Sanjeev Arora Nadav Cohen Elad Hazan 91 481 0 19 Feb 2018
To understand deep learning we need to understand kernel learning M. Belkin Siyuan Ma Soumik Mandal 47 418 0 05 Feb 2018
The Expressive Power of Neural Networks: A View from the Width Zhou Lu Hongming Pu Feicheng Wang Zhiqiang Hu Liwei Wang 72 886 0 08 Sep 2017
Exploring Generalization in Deep Learning Behnam Neyshabur Srinadh Bhojanapalli David A. McAllester Nathan Srebro FAtt 136 1,245 0 27 Jun 2017
Emergence of Invariance and Disentanglement in Deep Representations Alessandro Achille Stefano Soatto OOD DRL 75 473 0 05 Jun 2017
Towards Understanding the Invertibility of Convolutional Neural Networks A. Gilbert Yi Zhang Kibok Lee Y. Zhang Honglak Lee 38 64 0 24 May 2017
The power of deeper networks for expressing natural functions David Rolnick Max Tegmark 120 174 0 16 May 2017
The loss surface of deep and wide neural networks Quynh N. Nguyen Matthias Hein ODL 100 284 0 26 Apr 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 285 4,620 0 10 Nov 2016
Robust Large Margin Deep Neural Networks Jure Sokolić Raja Giryes Guillermo Sapiro M. Rodrigues 62 309 0 26 May 2016
Deep Learning without Poor Local Minima Kenji Kawaguchi ODL 173 922 0 23 May 2016
Benefits of depth in neural networks Matus Telgarsky 304 605 0 14 Feb 2016
The Power of Depth for Feedforward Neural Networks Ronen Eldan Ohad Shamir 168 731 0 12 Dec 2015
Path-SGD: Path-Normalized Optimization in Deep Neural Networks Behnam Neyshabur Ruslan Salakhutdinov Nathan Srebro ODL 65 305 0 08 Jun 2015
Deep Learning and the Information Bottleneck Principle Naftali Tishby Noga Zaslavsky DRL 145 1,570 0 09 Mar 2015
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 192 12,384 0 24 Jun 2012