Exploring Generalization in Deep Learning

27 June 2017

Srinadh Bhojanapalli

Papers citing "Exploring Generalization in Deep Learning"

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Title
Deep Ensemble as a Gaussian Process Approximate Posterior Zhijie Deng Feng Zhou Jianfei Chen Guoqiang Wu Jun Zhu UQCV 19 5 0 30 Apr 2022
U-NO: U-shaped Neural Operators Md Ashiqur Rahman Zachary E. Ross Kamyar Azizzadenesheli AI4CE 35 134 0 23 Apr 2022
Deep learning, stochastic gradient descent and diffusion maps Carmina Fjellström Kaj Nyström DiffM 20 14 0 04 Apr 2022
Exploiting Explainable Metrics for Augmented SGD Mahdi S. Hosseini Mathieu Tuli Konstantinos N. Plataniotis AAML 19 3 0 31 Mar 2022
Acknowledging the Unknown for Multi-label Learning with Single Positive Labels Donghao Zhou Pengfei Chen Qiong Wang Guangyong Chen Pheng-Ann Heng 25 28 0 30 Mar 2022
Random matrix analysis of deep neural network weight matrices M. Thamm Max Staats B. Rosenow 35 12 0 28 Mar 2022
Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point Bhargav Ganguly Seyyedali Hosseinalipour Kwang Taik Kim Christopher G. Brinton Vaneet Aggarwal David J. Love M. Chiang FedML 38 18 0 26 Mar 2022
Predicting the generalization gap in neural networks using topological data analysis Rubén Ballester Xavier Arnal Clemente Carles Casacuberta Meysam Madadi C. Corneanu Sergio Escalera 41 3 0 23 Mar 2022
Deep Learning Generalization, Extrapolation, and Over-parameterization Roozbeh Yousefzadeh 17 1 0 19 Mar 2022
Confidence Dimension for Deep Learning based on Hoeffding Inequality and Relative Evaluation Runqi Wang Linlin Yang Baochang Zhang Wentao Zhu David Doermann Guodong Guo 23 1 0 17 Mar 2022
Label-only Model Inversion Attack: The Attack that Requires the Least Information Dayong Ye Tianqing Zhu Shuai Zhou B. Liu Wanlei Zhou 22 4 0 13 Mar 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 29 47 0 11 Mar 2022
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization Xiuying Wei Ruihao Gong Yuhang Li Xianglong Liu F. Yu MQ VLM 19 167 0 11 Mar 2022
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks Nan Ding Xi Chen Tomer Levinboim Soravit Changpinyo Radu Soricut 22 26 0 10 Mar 2022
Flat minima generalize for low-rank matrix recovery Lijun Ding Dmitriy Drusvyatskiy Maryam Fazel Zaid Harchaoui 37 16 0 07 Mar 2022
$β$ -DARTS: Beta-Decay Regularization for Differentiable Architecture Search Peng Ye Baopu Li Yikang Li Tao Chen Jiayuan Fan Wanli Ouyang 16 102 0 03 Mar 2022
Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond Matan Schliserman Tomer Koren 24 23 0 27 Feb 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning A. Feder Cooper Emanuel Moss Benjamin Laufer Helen Nissenbaum MLAU 26 85 0 10 Feb 2022
The no-free-lunch theorems of supervised learning T. Sterkenburg Peter Grünwald FedML 24 56 0 09 Feb 2022
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning Yang Zhao Hao Zhang Xiuyuan Hu 38 116 0 08 Feb 2022
SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation Jun Xia Lirong Wu Jintao Chen Bozhen Hu Stan Z. Li 19 280 0 07 Feb 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data Yaoqing Yang Ryan Theisen Liam Hodgkinson Joseph E. Gonzalez Kannan Ramchandran Charles H. Martin Michael W. Mahoney 88 17 0 06 Feb 2022
Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto Hans Kersting F. Proske Francis R. Bach Aurelien Lucchi 64 44 0 06 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks Felix Biggs Benjamin Guedj BDL 30 26 0 03 Feb 2022
The Role of Linear Layers in Nonlinear Interpolating Networks Greg Ongie Rebecca Willett 63 15 0 02 Feb 2022
On the Power-Law Hessian Spectrums in Deep Learning Zeke Xie Qian-Yuan Tang Yunfeng Cai Mingming Sun P. Li ODL 42 9 0 31 Jan 2022
Implicit Regularization Towards Rank Minimization in ReLU Networks Nadav Timor Gal Vardi Ohad Shamir 34 49 0 30 Jan 2022
Monitoring Model Deterioration with Explainable Uncertainty Estimation via Non-parametric Bootstrap Carlos Mougan Dan Saattrup Nielsen 23 15 0 27 Jan 2022
Weight Expansion: A New Perspective on Dropout and Generalization Gao Jin Xinping Yi Pengfei Yang Lijun Zhang S. Schewe Xiaowei Huang 29 5 0 23 Jan 2022
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions Mojtaba Sahraee-Ardakan M. Emami Parthe Pandit S. Rangan A. Fletcher 41 9 0 20 Jan 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 25 34 0 20 Jan 2022
Neighborhood Region Smoothing Regularization for Finding Flat Minima In Deep Neural Networks Yang Zhao Hao Zhang 22 1 0 16 Jan 2022
Perspective Transformation Layer Nishant Khatri Agnibh Dasgupta Yucong Shen Xinru Zhong F. Shih 30 3 0 14 Jan 2022
On generalization bounds for deep networks based on loss surface implicit regularization Masaaki Imaizumi Johannes Schmidt-Hieber ODL 26 3 0 12 Jan 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg Sivaraman Balakrishnan Zachary Chase Lipton Behnam Neyshabur Hanie Sedghi OODD OOD 50 125 0 11 Jan 2022
Class-Incremental Continual Learning into the eXtended DER-verse Matteo Boschini Lorenzo Bonicelli Pietro Buzzega Angelo Porrello Simone Calderara CLL BDL 32 128 0 03 Jan 2022
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators Carles Domingo-Enrich MLT MDE 31 0 0 27 Dec 2021
Sparsest Univariate Learning Models Under Lipschitz Constraint Shayan Aziznejad Thomas Debarre M. Unser 21 4 0 27 Dec 2021
Risk bounds for aggregated shallow neural networks using Gaussian prior L. Tinsi A. Dalalyan BDL 20 7 0 21 Dec 2021
Visualizing the Loss Landscape of Winning Lottery Tickets Robert Bain UQCV 33 3 0 16 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 23 13 0 14 Dec 2021
Effective dimension of machine learning models Amira Abbas David Sutter Alessio Figalli Stefan Woerner 82 17 0 09 Dec 2021
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks Ekkehard Schnoor Arash Behboodi Holger Rauhut 18 13 0 08 Dec 2021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks P. Esser L. C. Vankadara D. Ghoshdastidar 28 53 0 07 Dec 2021
Multi-scale Feature Learning Dynamics: Insights for Double Descent Mohammad Pezeshki Amartya Mitra Yoshua Bengio Guillaume Lajoie 61 25 0 06 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 43 16 0 05 Dec 2021
Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent Wei Zhang Mingrui Liu Yu Feng Xiaodong Cui Brian Kingsbury Yuhai Tu 22 3 0 02 Dec 2021
Neuron with Steady Response Leads to Better Generalization Qiang Fu Lun Du Haitao Mao Xu Chen Wei Fang Shi Han Dongmei Zhang 33 5 0 30 Nov 2021