Fast generalization error bound of deep learning without scale invariance of activation functions

25 July 2019

Papers citing "Fast generalization error bound of deep learning without scale invariance of activation functions"

26 / 26 papers shown

Title
Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space Taiji Suzuki Atsushi Nitanda 38 61 0 28 Oct 2019
Deep ReLU network approximation of functions on a manifold Johannes Schmidt-Hieber 44 92 0 02 Aug 2019
Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality Ryumei Nakada Masaaki Imaizumi AI4CE 26 38 0 04 Jul 2019
On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces Satoshi Hayakawa Taiji Suzuki 18 48 0 22 May 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 117 769 0 12 Nov 2018
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality Taiji Suzuki 102 243 0 18 Oct 2018
Approximation and Estimation for High-Dimensional Deep Learning Networks Andrew R. Barron Jason M. Klusowski 40 59 0 10 Sep 2018
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error Taiji Suzuki Hiroshi Abe Tomoya Murata Shingo Horiuchi Kotaro Ito Tokuma Wachi So Hirai Masatoshi Yukishima Tomoaki Nishimura MLT 36 10 0 26 Aug 2018
Deep Neural Networks Learn Non-Smooth Functions Effectively Masaaki Imaizumi Kenji Fukumizu 116 123 0 13 Feb 2018
Optimal approximation of piecewise smooth functions using deep ReLU neural networks P. Petersen Felix Voigtländer 162 473 0 15 Sep 2017
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 121 805 0 22 Aug 2017
Exploring Generalization in Deep Learning Behnam Neyshabur Srinadh Bhojanapalli David A. McAllester Nathan Srebro FAtt 132 1,245 0 27 Jun 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 130 1,208 0 26 Jun 2017
Fast learning rate of deep learning via a kernel perspective Taiji Suzuki 37 6 0 29 May 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks Peter L. Bartlett Nick Harvey Christopher Liaw Abbas Mehrabian 140 427 0 08 Mar 2017
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 135 1,226 0 03 Oct 2016
Exponential expressivity in deep neural networks through transient chaos Ben Poole Subhaneil Lahiri M. Raghu Jascha Narain Sohl-Dickstein Surya Ganguli 78 587 0 16 Jun 2016
The Power of Depth for Feedforward Neural Networks Ronen Eldan Ohad Shamir 143 731 0 12 Dec 2015
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 207 5,502 0 23 Nov 2015
On the Expressive Power of Deep Learning: A Tensor Analysis Nadav Cohen Or Sharir Amnon Shashua 65 469 0 16 Sep 2015
Neural Network with Unbounded Activation Functions is Universal Approximator Sho Sonoda Noboru Murata 49 335 0 14 May 2015
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 223 583 0 27 Feb 2015
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 116 703 0 30 Dec 2014
On the Number of Linear Regions of Deep Neural Networks Guido Montúfar Razvan Pascanu Kyunghyun Cho Yoshua Bengio 72 1,250 0 08 Feb 2014
Statistical performance of support vector machines Gilles Blanchard Olivier Bousquet P. Massart 193 162 0 03 Apr 2008
Rejoinder: 2004 IMS Medallion Lecture: Local Rademacher complexities and oracle inequalities in risk minimization V. Koltchinskii 290 196 0 01 Aug 2007