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
Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data Colin Wei Kendrick Shen Yining Chen Tengyu Ma SSL 23 226 0 07 Oct 2020
Improved generalization by noise enhancement Takashi Mori Masahito Ueda 24 3 0 28 Sep 2020
Learning Optimal Representations with the Decodable Information Bottleneck Yann Dubois Douwe Kiela D. Schwab Ramakrishna Vedantam 31 43 0 27 Sep 2020
MSR-DARTS: Minimum Stable Rank of Differentiable Architecture Search Kengo Machida Kuniaki Uto Koichi Shinoda Taiji Suzuki 17 0 0 19 Sep 2020
Achieving Adversarial Robustness via Sparsity Shu-Fan Wang Ningyi Liao Liyao Xiang Nanyang Ye Quanshi Zhang AAML 14 14 0 11 Sep 2020
On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks Reda Marzouk 12 2 0 10 Sep 2020
Higher-order Quasi-Monte Carlo Training of Deep Neural Networks M. Longo Suman Mishra T. Konstantin Rusch Christoph Schwab 38 20 0 06 Sep 2020
HALO: Learning to Prune Neural Networks with Shrinkage Skyler Seto M. Wells Wenyu Zhang 24 0 0 24 Aug 2020
Generalization Guarantees for Imitation Learning Allen Z. Ren Sushant Veer Anirudha Majumdar 11 1 0 05 Aug 2020
Making Coherence Out of Nothing At All: Measuring the Evolution of Gradient Alignment S. Chatterjee Piotr Zielinski 10 8 0 03 Aug 2020
Generalization Comparison of Deep Neural Networks via Output Sensitivity Mahsa Forouzesh Farnood Salehi Patrick Thiran 14 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 36 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 19 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 27 21 0 11 Jul 2020
Meta-Learning with Network Pruning Hongduan Tian Bo Liu Xiaotong Yuan Qingshan Liu 27 27 0 07 Jul 2020
Are Labels Always Necessary for Classifier Accuracy Evaluation? Weijian Deng Liang Zheng 29 114 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 19 9 0 04 Jul 2020
Self-supervised Neural Architecture Search Sapir Kaplan Raja Giryes SSL 30 12 0 03 Jul 2020
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks Kyungsu Kim A. Lozano Eunho Yang AAML 40 0 0 02 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs Siddhartha Mishra Roberto Molinaro PINN 30 171 0 29 Jun 2020
Is SGD a Bayesian sampler? Well, almost Chris Mingard Guillermo Valle Pérez Joar Skalse A. Louis BDL 23 51 0 26 Jun 2020
Continual Learning from the Perspective of Compression Xu He Min Lin CLL 14 3 0 26 Jun 2020
A Limitation of the PAC-Bayes Framework Roi Livni Shay Moran 17 23 0 24 Jun 2020
Revisiting minimum description length complexity in overparameterized models Raaz Dwivedi Chandan Singh Bin Yu Martin J. Wainwright 14 4 0 17 Jun 2020
Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets Roozbeh Yousefzadeh Furong Huang 19 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 37 31 0 15 Jun 2020
Tangent Space Sensitivity and Distribution of Linear Regions in ReLU Networks Balint Daroczy AAML 6 0 0 11 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels Jun Shu Qian Zhao Zengben Xu Deyu Meng NoLa 33 29 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 17 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 30 39 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 39 631 0 09 Jun 2020
Pruning via Iterative Ranking of Sensitivity Statistics Stijn Verdenius M. Stol Patrick Forré AAML 24 37 0 01 Jun 2020
Enhancing accuracy of deep learning algorithms by training with low-discrepancy sequences Siddhartha Mishra T. Konstantin Rusch 27 49 0 26 May 2020
Is deeper better? It depends on locality of relevant features Takashi Mori Masahito Ueda OOD 25 4 0 26 May 2020
Learning the gravitational force law and other analytic functions Atish Agarwala Abhimanyu Das Rina Panigrahy Qiuyi Zhang MLT 16 0 0 15 May 2020
Computing the Testing Error without a Testing Set C. Corneanu Meysam Madadi Sergio Escalera Aleix M. Martinez AAML 10 69 0 01 May 2020
Local Lipschitz Bounds of Deep Neural Networks Calypso Herrera Florian Krach Josef Teichmann 19 3 0 27 Apr 2020
Evolution of Q Values for Deep Q Learning in Stable Baselines M. Andrews Cemil Dibek Karina Palyutina 11 3 0 24 Apr 2020
Deep Networks as Logical Circuits: Generalization and Interpretation Christopher Snyder S. Vishwanath FAtt AI4CE 11 2 0 25 Mar 2020
Hyperplane Arrangements of Trained ConvNets Are Biased Matteo Gamba S. Carlsson Hossein Azizpour Mårten Björkman 29 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 11 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 37 139 0 12 Mar 2020
Analyzing Visual Representations in Embodied Navigation Tasks Erik Wijmans Julian Straub Dhruv Batra Irfan Essa Judy Hoffman Ari S. Morcos 19 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 8 28 0 09 Mar 2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning Alex Renda Jonathan Frankle Michael Carbin 235 383 0 05 Mar 2020
Towards Probability-based Safety Verification of Systems with Components from Machine Learning H. Kaindl Stefan Kramer 25 1 0 02 Mar 2020
The Implicit and Explicit Regularization Effects of Dropout Colin Wei Sham Kakade Tengyu Ma 30 114 0 28 Feb 2020
Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers Zhuohan Li Eric Wallace Sheng Shen Kevin Lin Kurt Keutzer Dan Klein Joseph E. Gonzalez 22 148 0 26 Feb 2020
Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization S. Chatterjee ODL OOD 11 51 0 25 Feb 2020
De-randomized PAC-Bayes Margin Bounds: Applications to Non-convex and Non-smooth Predictors A. Banerjee Tiancong Chen Yingxue Zhou BDL 22 8 0 23 Feb 2020