A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks

29 July 2017

Srinadh Bhojanapalli

Papers citing "A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks"

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Title
Information-Theoretic Local Minima Characterization and Regularization Zhiwei Jia Hao Su 27 19 0 19 Nov 2019
On Generalization Bounds of a Family of Recurrent Neural Networks Minshuo Chen Xingguo Li T. Zhao 19 70 0 28 Oct 2019
Generalization Bounds for Neural Networks via Approximate Description Length Amit Daniely Elad Granot 28 20 0 13 Oct 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
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks Spencer Frei Yuan Cao Quanquan Gu ODL 9 31 0 07 Oct 2019
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks Yu Bai J. Lee 24 116 0 03 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 38 1 0 02 Oct 2019
A Constructive Prediction of the Generalization Error Across Scales Jonathan S. Rosenfeld Amir Rosenfeld Yonatan Belinkov Nir Shavit 36 205 0 27 Sep 2019
PAC-Bayes with Backprop Omar Rivasplata Vikram Tankasali Csaba Szepesvári 21 49 0 19 Aug 2019
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization Xinyan Li Qilong Gu Yingxue Zhou Tiancong Chen A. Banerjee ODL 42 51 0 24 Jul 2019
On improving deep learning generalization with adaptive sparse connectivity Shiwei Liu Decebal Constantin Mocanu Mykola Pechenizkiy ODL 20 7 0 27 Jun 2019
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets Amir-Reza Asadi Emmanuel Abbe BDL AI4CE 36 13 0 26 Jun 2019
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 52 322 0 13 Jun 2019
Are Anchor Points Really Indispensable in Label-Noise Learning? Xiaobo Xia Tongliang Liu N. Wang Bo Han Chen Gong Gang Niu Masashi Sugiyama NoLa 11 369 0 01 Jun 2019
PAC-Bayes Un-Expected Bernstein Inequality Zakaria Mhammedi Peter Grünwald Benjamin Guedj 21 46 0 31 May 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks Yuan Cao Quanquan Gu MLT AI4CE 17 383 0 30 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
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 14 236 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
Fine-grained Optimization of Deep Neural Networks Mete Ozay ODL 14 1 0 22 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 25 109 0 09 May 2019
Wasserstein Dependency Measure for Representation Learning Sherjil Ozair Corey Lynch Yoshua Bengio Aaron van den Oord Sergey Levine P. Sermanet SSL DRL 30 116 0 28 Mar 2019
Generalization Bounds For Unsupervised and Semi-Supervised Learning With Autoencoders Baruch Epstein Ron Meir SSL DRL AI4CE 10 16 0 04 Feb 2019
Asymmetric Valleys: Beyond Sharp and Flat Local Minima Haowei He Gao Huang Yang Yuan ODL MLT 28 147 0 02 Feb 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
Generalization in Deep Networks: The Role of Distance from Initialization Vaishnavh Nagarajan J. Zico Kolter ODL 4 95 0 07 Jan 2019
On a Sparse Shortcut Topology of Artificial Neural Networks Fenglei Fan Dayang Wang Hengtao Guo Qikui Zhu Pingkun Yan Ge Wang Hengyong Yu 38 22 0 22 Nov 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
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 27 271 0 19 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 15 68 0 13 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 14 765 0 12 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 23 245 0 12 Oct 2018
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units Yixi Xu Tianlin Li MQ 31 12 0 03 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 11 15 0 30 Sep 2018
Maximum-Entropy Fine-Grained Classification Abhimanyu Dubey O. Gupta Ramesh Raskar Nikhil Naik 28 156 0 16 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 18 62 0 11 Sep 2018
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 32 109 0 03 Aug 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate M. Belkin Daniel J. Hsu P. Mitra AI4CE 30 256 0 13 Jun 2018
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond Xingguo Li Junwei Lu Zhaoran Wang Jarvis Haupt T. Zhao 27 78 0 13 Jun 2018
PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments Anirudha Majumdar M. Goldstein Anoopkumar Sonar 23 18 0 11 Jun 2018
Minnorm training: an algorithm for training over-parameterized deep neural networks Yamini Bansal Madhu S. Advani David D. Cox Andrew M. Saxe ODL 15 18 0 03 Jun 2018
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network? S. Du Yining Wang Xiyu Zhai Sivaraman Balakrishnan Ruslan Salakhutdinov Aarti Singh SSL 21 57 0 21 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 44 209 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 25 79 0 15 Apr 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 26 630 0 14 Feb 2018
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent Yifan Wu Barnabás Póczós Aarti Singh MLT 27 8 0 13 Feb 2018
Learning Compact Neural Networks with Regularization Samet Oymak MLT 41 39 0 05 Feb 2018
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors Gintare Karolina Dziugaite Daniel M. Roy MLT 30 144 0 26 Dec 2017