Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach

16 April 2018

Papers citing "Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach"

50 / 155 papers shown

Title
For self-supervised learning, Rationality implies generalization, provably Yamini Bansal Gal Kaplun Boaz Barak OOD SSL 58 22 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 6 40 0 12 Oct 2020
Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks Yikai Wu Xingyu Zhu Chenwei Wu Annie Wang Rong Ge 24 42 0 08 Oct 2020
Neural Complexity Measures Yoonho Lee Juho Lee Sung Ju Hwang Eunho Yang Seungjin Choi 28 8 0 07 Aug 2020
Tighter risk certificates for neural networks Maria Perez-Ortiz Omar Rivasplata John Shawe-Taylor Csaba Szepesvári UQCV 20 102 0 25 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 11 0 0 15 Jul 2020
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks Kyungsu Kim A. Lozano Eunho Yang AAML 27 0 0 02 Jul 2020
Is SGD a Bayesian sampler? Well, almost Chris Mingard Guillermo Valle Pérez Joar Skalse A. Louis BDL 18 51 0 26 Jun 2020
Maximum Multiscale Entropy and Neural Network Regularization Amir-Reza Asadi Emmanuel Abbe 15 1 0 25 Jun 2020
Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks Felix Biggs Benjamin Guedj FedML UQCV BDL 14 34 0 22 Jun 2020
On the role of data in PAC-Bayes bounds Gintare Karolina Dziugaite Kyle Hsu W. Gharbieh Gabriel Arpino Daniel M. Roy 8 77 0 19 Jun 2020
PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons Xinjie Lan Xin Guo Kenneth Barner 19 3 0 16 Jun 2020
Entropic gradient descent algorithms and wide flat minima Fabrizio Pittorino C. Lucibello Christoph Feinauer Gabriele Perugini Carlo Baldassi Elizaveta Demyanenko R. Zecchina ODL MLT 30 33 0 14 Jun 2020
Generalization Bounds via Information Density and Conditional Information Density Fredrik Hellström G. Durisi 27 65 0 16 May 2020
On the Benefits of Invariance in Neural Networks Clare Lyle Mark van der Wilk Marta Z. Kwiatkowska Y. Gal Benjamin Bloem-Reddy OOD BDL 25 91 0 01 May 2020
Deep Networks as Logical Circuits: Generalization and Interpretation Christopher Snyder S. Vishwanath FAtt AI4CE 6 2 0 25 Mar 2020
Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited Wesley J. Maddox Gregory W. Benton A. Wilson 14 61 0 04 Mar 2020
Think Global, Act Local: Relating DNN generalisation and node-level SNR Paul Norridge 6 1 0 11 Feb 2020
Understanding Generalization in Deep Learning via Tensor Methods Jingling Li Yanchao Sun Jiahao Su Taiji Suzuki Furong Huang 22 27 0 14 Jan 2020
Frivolous Units: Wider Networks Are Not Really That Wide Stephen Casper Xavier Boix Vanessa D’Amario Ling Guo Martin Schrimpf Kasper Vinken Gabriel Kreiman 20 19 0 10 Dec 2019
The intriguing role of module criticality in the generalization of deep networks Niladri S. Chatterji Behnam Neyshabur Hanie Sedghi 20 51 0 02 Dec 2019
Information-Theoretic Local Minima Characterization and Regularization Zhiwei Jia Hao Su 27 19 0 19 Nov 2019
What Do Compressed Deep Neural Networks Forget? Sara Hooker Aaron Courville Gregory Clark Yann N. Dauphin Andrea Frome 17 181 0 13 Nov 2019
Global Capacity Measures for Deep ReLU Networks via Path Sampling Ryan Theisen Jason M. Klusowski Huan Wang N. Keskar Caiming Xiong R. Socher 21 3 0 22 Oct 2019
On Warm-Starting Neural Network Training Jordan T. Ash Ryan P. Adams AI4CE 23 21 0 18 Oct 2019
Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network Taiji Suzuki Hiroshi Abe Tomoaki Nishimura AI4CE 20 43 0 25 Sep 2019
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation Konstantinos Pitas 11 8 0 06 Sep 2019
Minimum Description Length Revisited Peter Grünwald Teemu Roos 20 64 0 21 Aug 2019
Refactoring Neural Networks for Verification David Shriver Dong Xu Sebastian G. Elbaum Matthew B. Dwyer 11 7 0 06 Aug 2019
What does it mean to understand a neural network? Timothy Lillicrap Konrad Paul Kording 18 42 0 15 Jul 2019
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets Amir-Reza Asadi Emmanuel Abbe BDL AI4CE 34 13 0 26 Jun 2019
Understanding Generalization through Visualizations Yifan Jiang Z. Emam Micah Goldblum Liam H. Fowl J. K. Terry Furong Huang Tom Goldstein AI4CE 16 80 0 07 Jun 2019
Bayesian Evidential Deep Learning with PAC Regularization Manuel Haussmann S. Gerwinn M. Kandemir UQCV EDL BDL 6 1 0 03 Jun 2019
PAC-Bayesian Transportation Bound Kohei Miyaguchi 11 5 0 31 May 2019
PAC-Bayes Un-Expected Bernstein Inequality Zakaria Mhammedi Peter Grünwald Benjamin Guedj 21 46 0 31 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
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 12 235 0 28 May 2019
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks Gaël Letarte Pascal Germain Benjamin Guedj Franccois Laviolette MQ AI4CE UQCV 28 54 0 24 May 2019
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study Daniel S. Park Jascha Narain Sohl-Dickstein Quoc V. Le Samuel L. Smith 22 57 0 09 May 2019
Approximating exponential family models (not single distributions) with a two-network architecture Sean R. Bittner John P. Cunningham 17 4 0 18 Mar 2019
Generalisation in fully-connected neural networks for time series forecasting Anastasia Borovykh C. Oosterlee S. Bohté OOD AI4TS 16 3 0 14 Feb 2019
Uniform convergence may be unable to explain generalization in deep learning Vaishnavh Nagarajan J. Zico Kolter MoMe AI4CE 7 309 0 13 Feb 2019
Identity Crisis: Memorization and Generalization under Extreme Overparameterization Chiyuan Zhang Samy Bengio Moritz Hardt Michael C. Mozer Y. Singer 6 87 0 13 Feb 2019
Are All Layers Created Equal? Chiyuan Zhang Samy Bengio Y. Singer 20 140 0 06 Feb 2019
Asymmetric Valleys: Beyond Sharp and Flat Local Minima Haowei He Gao Huang Yang Yuan ODL MLT 20 147 0 02 Feb 2019
Information-Theoretic Understanding of Population Risk Improvement with Model Compression Yuheng Bu Weihao Gao Shaofeng Zou V. Veeravalli MedIm 8 15 0 27 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 37 962 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 20 74 0 15 Jan 2019
Sample Compression, Support Vectors, and Generalization in Deep Learning Christopher Snyder S. Vishwanath MLT 14 5 0 05 Nov 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 29 650 0 03 Aug 2018