Stronger generalization bounds for deep nets via a compression approach

14 February 2018

Papers citing "Stronger generalization bounds for deep nets via a compression approach"

50 / 440 papers shown

Title
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression E. Balda Arash Behboodi Niklas Koep R. Mathar AAML 21 7 0 03 Jun 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 19 317 0 31 May 2019
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience Vaishnavh Nagarajan J. Zico Kolter 24 100 0 30 May 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks Yuan Cao Quanquan Gu MLT AI4CE 37 383 0 30 May 2019
MaxiMin Active Learning in Overparameterized Model Classes} Mina Karzand Robert D. Nowak 14 20 0 29 May 2019
On the Generalization Gap in Reparameterizable Reinforcement Learning Huan Wang Stephan Zheng Caiming Xiong R. Socher 17 39 0 29 May 2019
Generalization bounds for deep convolutional neural networks Philip M. Long Hanie Sedghi MLT 42 89 0 29 May 2019
Norm-based generalisation bounds for multi-class convolutional neural networks Antoine Ledent Waleed Mustafa Yunwen Lei Marius Kloft 18 5 0 29 May 2019
Implicit Rugosity Regularization via Data Augmentation Daniel LeJeune Randall Balestriero Hamid Javadi Richard G. Baraniuk 12 4 0 28 May 2019
SGD on Neural Networks Learns Functions of Increasing Complexity Preetum Nakkiran Gal Kaplun Dimitris Kalimeris Tristan Yang Benjamin L. Edelman Fred Zhang Boaz Barak MLT 22 236 0 28 May 2019
Abstraction Mechanisms Predict Generalization in Deep Neural Networks Alex Gain H. Siegelmann AI4CE 22 6 0 27 May 2019
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness Pengzhan Jin Lu Lu Yifa Tang George Karniadakis 14 60 0 27 May 2019
Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks Guodong Zhang James Martens Roger C. Grosse ODL 22 124 0 27 May 2019
Identity Connections in Residual Nets Improve Noise Stability Shuzhi Yu Carlo Tomasi 11 6 0 27 May 2019
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations Alex Lamb Jonathan Binas Anirudh Goyal Sandeep Subramanian Ioannis Mitliagkas Denis Kazakov Yoshua Bengio Michael C. Mozer OOD 19 3 0 26 May 2019
How degenerate is the parametrization of neural networks with the ReLU activation function? Julius Berner Dennis Elbrächter Philipp Grohs ODL 33 28 0 23 May 2019
The role of invariance in spectral complexity-based generalization bounds Konstantinos Pitas Andreas Loukas Mike Davies P. Vandergheynst BDL 14 1 0 23 May 2019
Fine-grained Optimization of Deep Neural Networks Mete Ozay ODL 16 1 0 22 May 2019
Revisiting hard thresholding for DNN pruning Konstantinos Pitas Mike Davies P. Vandergheynst AAML 20 2 0 21 May 2019
The sharp, the flat and the shallow: Can weakly interacting agents learn to escape bad minima? N. Kantas P. Parpas G. Pavliotis ODL 24 8 0 10 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 25 109 0 09 May 2019
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks Mingchen Li Mahdi Soltanolkotabi Samet Oymak NoLa 47 351 0 27 Mar 2019
Approximation and Non-parametric Estimation of ResNet-type Convolutional Neural Networks Kenta Oono Taiji Suzuki 35 58 0 24 Mar 2019
Deep learning observables in computational fluid dynamics K. Lye Siddhartha Mishra Deep Ray OOD AI4CE 21 158 0 07 Mar 2019
A Priori Estimates of the Population Risk for Residual Networks E. Weinan Chao Ma Qingcan Wang UQCV 40 61 0 06 Mar 2019
Implicit Regularization in Over-parameterized Neural Networks M. Kubo Ryotaro Banno Hidetaka Manabe Masataka Minoji 25 23 0 05 Mar 2019
Copying Machine Learning Classifiers Irene Unceta Jordi Nin O. Pujol 14 18 0 05 Mar 2019
Uniform convergence may be unable to explain generalization in deep learning Vaishnavh Nagarajan J. Zico Kolter MoMe AI4CE 17 310 0 13 Feb 2019
Identity Crisis: Memorization and Generalization under Extreme Overparameterization Chiyuan Zhang Samy Bengio Moritz Hardt Michael C. Mozer Y. Singer 14 88 0 13 Feb 2019
Towards moderate overparameterization: global convergence guarantees for training shallow neural networks Samet Oymak Mahdi Soltanolkotabi 19 319 0 12 Feb 2019
Task2Vec: Task Embedding for Meta-Learning Alessandro Achille Michael Lam Rahul Tewari Avinash Ravichandran Subhransu Maji Charless C. Fowlkes Stefano Soatto Pietro Perona SSL 28 309 0 10 Feb 2019
Are All Layers Created Equal? Chiyuan Zhang Samy Bengio Y. Singer 20 140 0 06 Feb 2019
Generalization Bounds For Unsupervised and Semi-Supervised Learning With Autoencoders Baruch Epstein Ron Meir SSL DRL AI4CE 16 16 0 04 Feb 2019
Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks Yuan Cao Quanquan Gu ODL MLT AI4CE 25 155 0 04 Feb 2019
Asymmetric Valleys: Beyond Sharp and Flat Local Minima Haowei He Gao Huang Yang Yuan ODL MLT 28 148 0 02 Feb 2019
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning Jian Li Xuanyuan Luo Mingda Qiao 27 85 0 02 Feb 2019
Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise Mayank Sharma Aayush Yadav Sumit Soman Jayadeva Jayadeva 4 1 0 31 Jan 2019
Deep Learning for Inverse Problems: Bounds and Regularizers Jaweria Amjad Zhaoyang Lyu M. Rodrigues 13 4 0 31 Jan 2019
Sample Complexity Bounds for Recurrent Neural Networks with Application to Combinatorial Graph Problems Nil-Jana Akpinar Bernhard Kratzwald Stefan Feuerriegel GNN 15 9 0 29 Jan 2019
Generalisation dynamics of online learning in over-parameterised neural networks Sebastian Goldt Madhu S. Advani Andrew M. Saxe Florent Krzakala Lenka Zdeborová 33 14 0 25 Jan 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
Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks Charles H. Martin Michael W. Mahoney 15 55 0 24 Jan 2019
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis Yusuke Tsuzuku Issei Sato Masashi Sugiyama 25 75 0 15 Jan 2019
How Compact?: Assessing Compactness of Representations through Layer-Wise Pruning Hyun-Joo Jung Jaedeok Kim Yoonsuck Choe 16 1 0 09 Jan 2019
Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution Shen-Huan Lyu Lu Wang Zhi-Hua Zhou 30 11 0 27 Dec 2018
Towards a Theoretical Understanding of Hashing-Based Neural Nets Yibo Lin Zhao Song Lin F. Yang 22 5 0 26 Dec 2018
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? Samet Oymak Mahdi Soltanolkotabi ODL 6 176 0 25 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
Generalizable Adversarial Training via Spectral Normalization Farzan Farnia Jesse M. Zhang David Tse OOD AAML 45 138 0 19 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 18 68 0 13 Nov 2018