Exploring Generalization in Deep Learning

27 June 2017

Srinadh Bhojanapalli

Papers citing "Exploring Generalization in Deep Learning"

50 / 305 papers shown

Title
Synthetic Data -- what, why and how? James Jordon Lukasz Szpruch F. Houssiau M. Bottarelli Giovanni Cherubin Carsten Maple Samuel N. Cohen Adrian Weller 40 109 0 06 May 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 26 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 19 166 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
$β$ -DARTS: Beta-Decay Regularization for Differentiable Architecture Search Peng Ye Baopu Li Yikang Li Tao Chen Jiayuan Fan Wanli Ouyang 16 101 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 24 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 30 116 0 08 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 86 17 0 06 Feb 2022
Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto Hans Kersting F. Proske Francis R. Bach Aurelien Lucchi 53 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
On the Power-Law Hessian Spectrums in Deep Learning Zeke Xie Qian-Yuan Tang Yunfeng Cai Mingming Sun P. Li ODL 42 8 0 31 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 25 3 0 14 Jan 2022
Class-Incremental Continual Learning into the eXtended DER-verse Matteo Boschini Lorenzo Bonicelli Pietro Buzzega Angelo Porrello Simone Calderara CLL BDL 26 128 0 03 Jan 2022
Visualizing the Loss Landscape of Winning Lottery Tickets Robert Bain UQCV 25 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 20 13 0 14 Dec 2021
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks Ekkehard Schnoor Arash Behboodi Holger Rauhut 16 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 38 16 0 05 Dec 2021
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks Tolga Birdal Aaron Lou Leonidas J. Guibas Umut cSimcsekli 27 61 0 25 Nov 2021
Subspace Adversarial Training Tao Li Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML OOD 41 56 0 24 Nov 2021
Discovering and Explaining the Representation Bottleneck of DNNs Huiqi Deng Qihan Ren Hao Zhang Quanshi Zhang 39 59 0 11 Nov 2021
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Lun Du Xiaozhou Shi Qiang Fu Xiaojun Ma Hengyu Liu Shi Han Dongmei Zhang 37 104 0 29 Oct 2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization Sihyun Yu Sungsoo Ahn Le Song Jinwoo Shin OffRL 27 31 0 27 Oct 2021
Does the Data Induce Capacity Control in Deep Learning? Rubing Yang J. Mao Pratik Chaudhari 27 15 0 27 Oct 2021
In Search of Probeable Generalization Measures Jonathan Jaegerman Khalil Damouni M. M. Ankaralı Konstantinos N. Plataniotis 19 2 0 23 Oct 2021
Behavioral Experiments for Understanding Catastrophic Forgetting Samuel J. Bell Neil D. Lawrence 27 4 0 20 Oct 2021
Interpretive Blindness Nicholas M. Asher Julie Hunter 11 0 0 19 Oct 2021
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks R. Entezari Hanie Sedghi O. Saukh Behnam Neyshabur MoMe 37 215 0 12 Oct 2021
New Insights into Graph Convolutional Networks using Neural Tangent Kernels Mahalakshmi Sabanayagam P. Esser D. Ghoshdastidar 21 6 0 08 Oct 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 56 18 0 07 Oct 2021
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications Ziqiao Wang Yongyi Mao FedML MLT 37 22 0 07 Oct 2021
On Margin Maximization in Linear and ReLU Networks Gal Vardi Ohad Shamir Nathan Srebro 50 28 0 06 Oct 2021
VC dimension of partially quantized neural networks in the overparametrized regime Yutong Wang Clayton D. Scott 17 1 0 06 Oct 2021
Spectral Bias in Practice: The Role of Function Frequency in Generalization Sara Fridovich-Keil Raphael Gontijo-Lopes Rebecca Roelofs 41 28 0 06 Oct 2021
On the Impact of Stable Ranks in Deep Nets B. Georgiev L. Franken Mayukh Mukherjee Georgios Arvanitidis 13 3 0 05 Oct 2021
Exploring the Limits of Large Scale Pre-training Samira Abnar Mostafa Dehghani Behnam Neyshabur Hanie Sedghi AI4CE 60 114 0 05 Oct 2021
Perturbated Gradients Updating within Unit Space for Deep Learning Ching-Hsun Tseng Liu Cheng Shin-Jye Lee Xiaojun Zeng 40 5 0 01 Oct 2021
Adversarial Parameter Defense by Multi-Step Risk Minimization Zhiyuan Zhang Ruixuan Luo Xuancheng Ren Qi Su Liangyou Li Xu Sun AAML 23 6 0 07 Sep 2021
Benchmarking the Robustness of Instance Segmentation Models Said Fahri Altindis Yusuf Dalva Hamza Pehlivan Aysegül Dündar VLM OOD 29 12 0 02 Sep 2021
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks Haekyu Park Nilaksh Das Rahul Duggal Austin P. Wright Omar Shaikh Fred Hohman Duen Horng Chau HAI 19 25 0 29 Aug 2021
A Scaling Law for Synthetic-to-Real Transfer: How Much Is Your Pre-training Effective? Hiroaki Mikami Kenji Fukumizu Shogo Murai Shuji Suzuki Yuta Kikuchi Taiji Suzuki S. Maeda Kohei Hayashi 40 12 0 25 Aug 2021
Influence-guided Data Augmentation for Neural Tensor Completion Sejoon Oh Sungchul Kim Ryan A. Rossi Srijan Kumar 22 10 0 23 Aug 2021
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering Nairouz Mrabah Mohamed Bouguessa M. Touati Riadh Ksantini 35 62 0 19 Jul 2021