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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 / 444 papers shown

Title
An Investigation of how Label Smoothing Affects Generalization Blair Chen Liu Ziyin Zihao Wang Paul Pu Liang UQCV 92 18 0 23 Oct 2020
Deep Learning is Singular, and That's Good Daniel Murfet Susan Wei Biwei Huang Hui Li Jesse Gell-Redman T. Quella UQCV 83 29 0 22 Oct 2020
Learning Curves for Analysis of Deep Networks Derek Hoiem Tanmay Gupta Zhizhong Li Michal Shlapentokh-Rothman 87 26 0 21 Oct 2020
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers Preetum Nakkiran Behnam Neyshabur Hanie Sedghi OffRL 104 11 0 16 Oct 2020
How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks Gao Jin Xinping Yi Liang Zhang Lijun Zhang S. Schewe Xiaowei Huang 88 42 0 12 Oct 2020
How Does Mixup Help With Robustness and Generalization? Linjun Zhang Zhun Deng Kenji Kawaguchi Amirata Ghorbani James Zou AAML 121 252 0 09 Oct 2020
Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data Colin Wei Kendrick Shen Yining Chen Tengyu Ma SSL 133 232 0 07 Oct 2020
Improved generalization by noise enhancement Takashi Mori Masahito Ueda 52 3 0 28 Sep 2020
Learning Optimal Representations with the Decodable Information Bottleneck Yann Dubois Douwe Kiela D. Schwab Ramakrishna Vedantam 122 43 0 27 Sep 2020
MSR-DARTS: Minimum Stable Rank of Differentiable Architecture Search Kengo Machida Kuniaki Uto Koichi Shinoda Taiji Suzuki 42 0 0 19 Sep 2020
Achieving Adversarial Robustness via Sparsity Shu-Fan Wang Ningyi Liao Liyao Xiang Nanyang Ye Quanshi Zhang AAML 58 16 0 11 Sep 2020
On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks Reda Marzouk 60 2 0 10 Sep 2020
Higher-order Quasi-Monte Carlo Training of Deep Neural Networks M. Longo Suman Mishra T. Konstantin Rusch Christoph Schwab 74 21 0 06 Sep 2020
HALO: Learning to Prune Neural Networks with Shrinkage Skyler Seto M. Wells Wenyu Zhang 80 0 0 24 Aug 2020
Generalization Guarantees for Imitation Learning Allen Z. Ren Sushant Veer Anirudha Majumdar 47 1 0 05 Aug 2020
Making Coherence Out of Nothing At All: Measuring the Evolution of Gradient Alignment S. Chatterjee Piotr Zielinski 59 8 0 03 Aug 2020
Generalization Comparison of Deep Neural Networks via Output Sensitivity Mahsa Forouzesh Farnood Salehi Patrick Thiran 44 8 0 30 Jul 2020
Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems Donsub Rim Luca Venturi Joan Bruna Benjamin Peherstorfer 83 9 0 28 Jul 2020
From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines A. Shilton Sunil Gupta Santu Rana Svetha Venkatesh 38 0 0 15 Jul 2020
Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics Taiji Suzuki 65 21 0 11 Jul 2020
Meta-Learning with Network Pruning Hongduan Tian Bo Liu Xiaotong Yuan Qingshan Liu 70 27 0 07 Jul 2020
Are Labels Always Necessary for Classifier Accuracy Evaluation? Weijian Deng Liang Zheng 74 118 0 06 Jul 2020
DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths Yanwei Fu Chen Liu Donghao Li Xinwei Sun Jinshan Zeng Yuan Yao 51 9 0 04 Jul 2020
Self-supervised Neural Architecture Search Sapir Kaplan Raja Giryes SSL 75 12 0 03 Jul 2020
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks Kyungsu Kim A. Lozano Eunho Yang AAML 105 0 0 02 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs Siddhartha Mishra Roberto Molinaro PINN 112 173 0 29 Jun 2020
Is SGD a Bayesian sampler? Well, almost Chris Mingard Guillermo Valle Pérez Joar Skalse A. Louis BDL 90 53 0 26 Jun 2020
Continual Learning from the Perspective of Compression Xu He Min Lin CLL 45 3 0 26 Jun 2020
A Limitation of the PAC-Bayes Framework Roi Livni Shay Moran 118 25 0 24 Jun 2020
Revisiting minimum description length complexity in overparameterized models Raaz Dwivedi Chandan Singh Bin Yu Martin J. Wainwright 83 5 0 17 Jun 2020
Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets Roozbeh Yousefzadeh Furong Huang 55 6 0 17 Jun 2020
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks Kenta Oono Taiji Suzuki AI4CE 149 32 0 15 Jun 2020
Tangent Space Sensitivity and Distribution of Linear Regions in ReLU Networks Balint Daroczy AAML 26 0 0 11 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels Jun Shu Qian Zhao Zengben Xu Deyu Meng NoLa 106 31 0 10 Jun 2020
Training with Multi-Layer Embeddings for Model Reduction Benjamin Ghaemmaghami Zihao Deng B. Cho Leo Orshansky A. Singh M. Erez Michael Orshansky 3DV 54 10 0 10 Jun 2020
Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption Xu Sun Zhiyuan Zhang Xuancheng Ren Ruixuan Luo Liangyou Li 73 40 0 10 Jun 2020
Pruning neural networks without any data by iteratively conserving synaptic flow Hidenori Tanaka D. Kunin Daniel L. K. Yamins Surya Ganguli 270 652 0 09 Jun 2020
Pruning via Iterative Ranking of Sensitivity Statistics Stijn Verdenius M. Stol Patrick Forré AAML 91 38 0 01 Jun 2020
Enhancing accuracy of deep learning algorithms by training with low-discrepancy sequences Siddhartha Mishra T. Konstantin Rusch 89 50 0 26 May 2020
Is deeper better? It depends on locality of relevant features Takashi Mori Masahito Ueda OOD 124 4 0 26 May 2020
Learning the gravitational force law and other analytic functions Atish Agarwala Abhimanyu Das Rina Panigrahy Qiuyi Zhang MLT 50 0 0 15 May 2020
Computing the Testing Error without a Testing Set C. Corneanu Meysam Madadi Sergio Escalera Aleix M. Martinez AAML 69 71 0 01 May 2020
Local Lipschitz Bounds of Deep Neural Networks Calypso Herrera Florian Krach Josef Teichmann 52 3 0 27 Apr 2020
Evolution of Q Values for Deep Q Learning in Stable Baselines M. Andrews Cemil Dibek Karina Palyutina 40 3 0 24 Apr 2020
Deep Networks as Logical Circuits: Generalization and Interpretation Christopher Snyder S. Vishwanath FAtt AI4CE 28 2 0 25 Mar 2020
Hyperplane Arrangements of Trained ConvNets Are Biased Matteo Gamba S. Carlsson Hossein Azizpour Mårten Björkman 41 5 0 17 Mar 2020
Weak and Strong Gradient Directions: Explaining Memorization, Generalization, and Hardness of Examples at Scale Piotr Zielinski Shankar Krishnan S. Chatterjee ODL 134 2 0 16 Mar 2020
Invariant Causal Prediction for Block MDPs Amy Zhang Clare Lyle Shagun Sodhani Angelos Filos Marta Z. Kwiatkowska Joelle Pineau Y. Gal Doina Precup OffRL AI4CE OOD 143 144 0 12 Mar 2020
Analyzing Visual Representations in Embodied Navigation Tasks Erik Wijmans Julian Straub Dhruv Batra Irfan Essa Judy Hoffman Ari S. Morcos 82 2 0 12 Mar 2020
Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule Nikhil Iyer V. Thejas Nipun Kwatra Ramachandran Ramjee Muthian Sivathanu 112 29 0 09 Mar 2020