A Theoretical-Empirical Approach to Estimating Sample Complexity of DNNs

5 May 2021

Papers citing "A Theoretical-Empirical Approach to Estimating Sample Complexity of DNNs"

19 / 19 papers shown

Title
Fantastic Generalization Measures and Where to Find Them Yiding Jiang Behnam Neyshabur H. Mobahi Dilip Krishnan Samy Bengio AI4CE 136 607 0 04 Dec 2019
Learning Curves for Deep Neural Networks: A Gaussian Field Theory Perspective Omry Cohen Orit Malka Zohar Ringel AI4CE 52 22 0 12 Jun 2019
Dimensionality compression and expansion in Deep Neural Networks Stefano Recanatesi M. Farrell Madhu S. Advani Timothy Moore Guillaume Lajoie E. Shea-Brown 60 73 0 02 Jun 2019
Asymptotic learning curves of kernel methods: empirical data v.s. Teacher-Student paradigm S. Spigler Mario Geiger Matthieu Wyart 68 38 0 26 May 2019
Estimating the intrinsic dimension of datasets by a minimal neighborhood information Elena Facco M. d’Errico Alex Rodriguez Alessandro Laio 49 327 0 19 Mar 2018
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle Rana Ali Amjad Bernhard C. Geiger 71 196 0 27 Feb 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 86 642 0 14 Feb 2018
State-of-the-art Speech Recognition With Sequence-to-Sequence Models Chung-Cheng Chiu Tara N. Sainath Yonghui Wu Rohit Prabhavalkar Patrick Nguyen ... Katya Gonina Navdeep Jaitly Yue Liu J. Chorowski M. Bacchiani AI4TS 89 1,153 0 05 Dec 2017
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 194 1,276 0 05 Oct 2017
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era Chen Sun Abhinav Shrivastava Saurabh Singh Abhinav Gupta VLM 188 2,401 0 10 Jul 2017
Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data Gintare Karolina Dziugaite Daniel M. Roy 106 815 0 31 Mar 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks Peter L. Bartlett Nick Harvey Christopher Liaw Abbas Mehrabian 208 432 0 08 Mar 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 339 4,629 0 10 Nov 2016
Joint Unsupervised Learning of Deep Representations and Image Clusters Jianwei Yang Devi Parikh Dhruv Batra SSL 54 817 0 13 Apr 2016
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 313 6,681 0 08 Jun 2015
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning Behnam Neyshabur Ryota Tomioka Nathan Srebro AI4CE 94 658 0 20 Dec 2014
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 558 27,311 0 01 Sep 2014
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation Emily L. Denton Wojciech Zaremba Joan Bruna Yann LeCun Rob Fergus FAtt 177 1,689 0 02 Apr 2014
Speech Recognition with Deep Recurrent Neural Networks Alex Graves Abdel-rahman Mohamed Geoffrey E. Hinton 226 8,517 0 22 Mar 2013