Exploring Generalization in Deep Learning

27 June 2017

Srinadh Bhojanapalli

Papers citing "Exploring Generalization in Deep Learning"

50 / 308 papers shown

Title
AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks Majed El Helou Frederike Dumbgen Sabine Süsstrunk CLL AI4CE 30 2 0 07 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 30 785 0 26 Feb 2020
Generalisation error in learning with random features and the hidden manifold model Federica Gerace Bruno Loureiro Florent Krzakala M. Mézard Lenka Zdeborová 25 165 0 21 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 24 639 0 20 Feb 2020
Data-Driven Symbol Detection via Model-Based Machine Learning Nariman Farsad Nir Shlezinger Andrea J. Goldsmith Yonina C. Eldar 21 49 0 14 Feb 2020
Topologically Densified Distributions Christoph Hofer Florian Graf Marc Niethammer Roland Kwitt 27 15 0 12 Feb 2020
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima Zeke Xie Issei Sato Masashi Sugiyama ODL 20 17 0 10 Feb 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 27 19 0 31 Dec 2019
Locality and compositionality in zero-shot learning Tristan Sylvain Linda Petrini R. Devon Hjelm 18 56 0 20 Dec 2019
Improving Model Robustness Using Causal Knowledge T. Kyono M. Schaar OOD 22 12 0 27 Nov 2019
Information-Theoretic Local Minima Characterization and Regularization Zhiwei Jia Hao Su 21 19 0 19 Nov 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 36 85 0 09 Oct 2019
How does topology influence gradient propagation and model performance of deep networks with DenseNet-type skip connections? Kartikeya Bhardwaj Guihong Li R. Marculescu 30 1 0 02 Oct 2019
A Constructive Prediction of the Generalization Error Across Scales Jonathan S. Rosenfeld Amir Rosenfeld Yonatan Belinkov Nir Shavit 22 205 0 27 Sep 2019
PAC-Bayes with Backprop Omar Rivasplata Vikram Tankasali Csaba Szepesvári 21 49 0 19 Aug 2019
On improving deep learning generalization with adaptive sparse connectivity Shiwei Liu D. Mocanu Mykola Pechenizkiy ODL 12 7 0 27 Jun 2019
The Barron Space and the Flow-induced Function Spaces for Neural Network Models E. Weinan Chao Ma Lei Wu 30 109 0 18 Jun 2019
Learning to Forget for Meta-Learning Sungyong Baik Seokil Hong Kyoung Mu Lee CLL KELM 14 87 0 13 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 21 481 0 12 Jun 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 24 8 0 10 Jun 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 24 491 0 31 May 2019
Generalization bounds for deep convolutional neural networks Philip M. Long Hanie Sedghi MLT 37 89 0 29 May 2019
Fine-grained Optimization of Deep Neural Networks Mete Ozay ODL 8 1 0 22 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 14 109 0 09 May 2019
Stability and Generalization of Graph Convolutional Neural Networks Saurabh Verma Zhi-Li Zhang GNN MLT 24 153 0 03 May 2019
Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning Alessandro Bianchi Moreno Raimondo Vendra P. Protopapas Marco Brambilla 12 8 0 08 Apr 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks L. Cardelli M. Kwiatkowska Luca Laurenti Nicola Paoletti A. Patané Matthew Wicker AAML 23 54 0 05 Mar 2019
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen Kevin Luk Maxime Gazeau Guodong Zhang Harris Chan Jimmy Ba ODL 20 22 0 21 Feb 2019
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module Tiago Ramalho M. Garnelo BDL 33 77 0 07 Feb 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 17 237 0 18 Jan 2019
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 22 446 0 21 Nov 2018
Neural Lander: Stable Drone Landing Control using Learned Dynamics Guanya Shi Xichen Shi Michael O'Connell Rose Yu Kamyar Azizzadenesheli Anima Anandkumar Yisong Yue Soon-Jo Chung 16 270 0 19 Nov 2018
A Priori Estimates of the Population Risk for Two-layer Neural Networks Weinan E Chao Ma Lei Wu 29 130 0 15 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei J. Lee Qiang Liu Tengyu Ma 18 243 0 12 Oct 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 32 190 0 02 Oct 2018
Fluctuation-dissipation relations for stochastic gradient descent Sho Yaida 19 73 0 28 Sep 2018
Capacity Control of ReLU Neural Networks by Basis-path Norm Shuxin Zheng Qi Meng Huishuai Zhang Wei-neng Chen Nenghai Yu Tie-Yan Liu 24 23 0 19 Sep 2018
Approximation and Estimation for High-Dimensional Deep Learning Networks Andrew R. Barron Jason M. Klusowski 24 59 0 10 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
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 23 109 0 03 Aug 2018
A Mean-Field Optimal Control Formulation of Deep Learning Weinan E Jiequn Han Qianxiao Li OOD 6 181 0 03 Jul 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min-Bin Lin Fred Hamprecht Yoshua Bengio Aaron Courville 39 1,390 0 22 Jun 2018
PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments Anirudha Majumdar M. Goldstein Anoopkumar Sonar 20 18 0 11 Jun 2018
Understanding Batch Normalization Johan Bjorck Carla P. Gomes B. Selman Kilian Q. Weinberger 18 593 0 01 Jun 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 17 515 0 28 May 2018
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach Wenda Zhou Victor Veitch Morgane Austern Ryan P. Adams Peter Orbanz 32 209 0 16 Apr 2018
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds Cenk Baykal Lucas Liebenwein Igor Gilitschenski Dan Feldman Daniela Rus 17 79 0 15 Apr 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 13 328 0 19 Mar 2018
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs Diviyan Kalainathan Olivier Goudet Isabelle M Guyon David Lopez-Paz Michèle Sebag CML 24 93 0 13 Mar 2018
A Walk with SGD Chen Xing Devansh Arpit Christos Tsirigotis Yoshua Bengio 19 118 0 24 Feb 2018