Understanding deep learning requires rethinking generalization

10 November 2016

Benjamin Recht

Papers citing "Understanding deep learning requires rethinking generalization"

50 / 1,102 papers shown

Title
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction Yaodong Yu Kwan Ho Ryan Chan Chong You Chaobing Song Yi Ma SSL 38 190 0 15 Jun 2020
Learning Bounds for Risk-sensitive Learning Jaeho Lee Sejun Park Jinwoo Shin 25 46 0 15 Jun 2020
Towards Robust Pattern Recognition: A Review Xu-Yao Zhang Cheng-Lin Liu C. Suen OOD HAI 26 103 0 12 Jun 2020
To Each Optimizer a Norm, To Each Norm its Generalization Sharan Vaswani Reza Babanezhad Jose Gallego Aaron Mishkin Simon Lacoste-Julien Nicolas Le Roux 26 8 0 11 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels Jun Shu Qian Zhao Zengben Xu Deyu Meng NoLa 33 30 0 10 Jun 2020
Probably Approximately Correct Constrained Learning Luiz F. O. Chamon Alejandro Ribeiro 22 38 0 09 Jun 2020
Provable tradeoffs in adversarially robust classification Yan Sun Hamed Hassani David Hong Alexander Robey 23 53 0 09 Jun 2020
The Curious Case of Convex Neural Networks S. Sivaprasad Ankur Singh Naresh Manwani Vineet Gandhi 46 27 0 09 Jun 2020
Rethinking Importance Weighting for Deep Learning under Distribution Shift Tongtong Fang Nan Lu Gang Niu Masashi Sugiyama 33 137 0 08 Jun 2020
Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation Jingyang Zhang Guotai Wang Hongzhi Xie Shuyang Zhang Ning Huang Shaoting Zhang Lixu Gu 35 41 0 27 May 2020
Data Separability for Neural Network Classifiers and the Development of a Separability Index Shuyue Guan Murray H. Loew Hanseok Ko 11 3 0 27 May 2020
Is deeper better? It depends on locality of relevant features Takashi Mori Masahito Ueda OOD 25 4 0 26 May 2020
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images Yixing Huang Alexander Preuhs M. Manhart G. Lauritsch Andreas Maier MedIm 27 5 0 20 May 2020
Classification vs regression in overparameterized regimes: Does the loss function matter? Vidya Muthukumar Adhyyan Narang Vignesh Subramanian M. Belkin Daniel J. Hsu A. Sahai 56 149 0 16 May 2020
Generalization Bounds via Information Density and Conditional Information Density Fredrik Hellström G. Durisi 27 65 0 16 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
Implicit Regularization in Deep Learning May Not Be Explainable by Norms Noam Razin Nadav Cohen 24 155 0 13 May 2020
Ensembled sparse-input hierarchical networks for high-dimensional datasets Jean Feng N. Simon 19 4 0 11 May 2020
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 155 372 0 09 May 2020
DQI: Measuring Data Quality in NLP Swaroop Mishra Anjana Arunkumar Bhavdeep Singh Sachdeva Chris Bryan Chitta Baral 38 30 0 02 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 33 92 0 01 May 2020
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization Zijie J. Wang Robert Turko Omar Shaikh Haekyu Park Nilaksh Das Fred Hohman Minsuk Kahng Duen Horng Chau HAI FAtt 35 240 0 30 Apr 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 55 371 0 30 Apr 2020
A Perspective on Deep Learning for Molecular Modeling and Simulations Jun Zhang Yao-Kun Lei Zhen Zhang Junhan Chang Maodong Li Xu Han Lijiang Yang Yue Yang Y. Gao AI4CE 42 8 0 25 Apr 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 51 172 0 23 Apr 2020
On the Compressive Power of Boolean Threshold Autoencoders A. Melkman Sini Guo W. Ching Pengyu Liu Tatsuya Akutsu AI4CE 16 3 0 21 Apr 2020
Unsupervised Person Re-identification via Multi-label Classification Dongkai Wang Shiliang Zhang 24 360 0 20 Apr 2020
OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer Xiaoxu Li Dongliang Chang Zhanyu Ma Zheng-Hua Tan Jing-Hao Xue Jie Cao Jingyi Yu Jun Guo 33 32 0 20 Apr 2020
How to Teach DNNs to Pay Attention to the Visual Modality in Speech Recognition George Sterpu Christian Saam N. Harte 34 28 0 17 Apr 2020
Divergent Search for Few-Shot Image Classification Jeremy Tan Bernhard Kainz 12 0 0 16 Apr 2020
A function space analysis of finite neural networks with insights from sampling theory Raja Giryes 25 6 0 15 Apr 2020
On Learning Rates and Schrödinger Operators Bin Shi Weijie J. Su Michael I. Jordan 34 60 0 15 Apr 2020
On the interplay between physical and content priors in deep learning for computational imaging Mo Deng Shuai Li Iksung Kang N. Fang George Barbastathis 39 26 0 14 Apr 2020
Gradient Centralization: A New Optimization Technique for Deep Neural Networks Hongwei Yong Jianqiang Huang Xiansheng Hua Lei Zhang ODL 32 184 0 03 Apr 2020
Self-Augmentation: Generalizing Deep Networks to Unseen Classes for Few-Shot Learning Jinhwan Seo Hong G Jung Seong-Whan Lee SSL 21 39 0 01 Apr 2020
A theory of independent mechanisms for extrapolation in generative models M. Besserve Rémy Sun Dominik Janzing Bernhard Schölkopf 28 25 0 01 Apr 2020
Information Leakage in Embedding Models Congzheng Song A. Raghunathan MIACV 27 263 0 31 Mar 2020
Regularizing Class-wise Predictions via Self-knowledge Distillation Sukmin Yun Jongjin Park Kimin Lee Jinwoo Shin 29 276 0 31 Mar 2020
Dataless Model Selection with the Deep Frame Potential Calvin Murdock Simon Lucey 41 6 0 30 Mar 2020
Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning Andreas Kirsch Clare Lyle Y. Gal 27 16 0 27 Mar 2020
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective Qilong Wang Li Zhang Banggu Wu Dongwei Ren P. Li W. Zuo Q. Hu 22 21 0 25 Mar 2020
Learn to Forget: Machine Unlearning via Neuron Masking Yang Liu Zhuo Ma Ximeng Liu Jian-wei Liu Zhongyuan Jiang Jianfeng Ma Philip Yu K. Ren MU 27 61 0 24 Mar 2020
Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives Duo Li Qifeng Chen 153 19 0 24 Mar 2020
Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses Charles G. Frye James B. Simon Neha S. Wadia A. Ligeralde M. DeWeese K. Bouchard ODL 16 2 0 23 Mar 2020
On Calibration of Mixup Training for Deep Neural Networks Juan Maroñas D. Ramos-Castro Roberto Paredes Palacios UQCV 33 6 0 22 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 26 7 0 17 Mar 2020
What Information Does a ResNet Compress? L. N. Darlow Amos Storkey SSL 32 11 0 13 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
SASL: Saliency-Adaptive Sparsity Learning for Neural Network Acceleration Jun Shi Jianfeng Xu K. Tasaka Zhibo Chen 8 25 0 12 Mar 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth Yiping Lu Chao Ma Yulong Lu Jianfeng Lu Lexing Ying MLT 41 78 0 11 Mar 2020