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Information-Theoretic Generalization Bounds for Transductive Learning and its Applications

8 November 2023

Papers citing "Information-Theoretic Generalization Bounds for Transductive Learning and its Applications"

50 / 87 papers shown

Title
Sharp Generalization of Transductive Learning: A Transductive Local Rademacher Complexity Approach Yingzhen Yang 87 4 0 28 Sep 2023
Generalization Bounds: Perspectives from Information Theory and PAC-Bayes Fredrik Hellström G. Durisi Benjamin Guedj Maxim Raginsky 55 38 0 08 Sep 2023
Sharpness-Aware Graph Collaborative Filtering Huiyuan Chen Chin-Chia Michael Yeh Yujie Fan Yan Zheng Junpeng Wang Vivian Lai Mahashweta Das Hao Yang 75 5 0 18 Jul 2023
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund 146 9 0 21 Jun 2023
How Does Information Bottleneck Help Deep Learning? Kenji Kawaguchi Zhun Deng Xu Ji Jiaoyang Huang 93 62 0 30 May 2023
Towards Understanding the Generalization of Graph Neural Networks Huayi Tang Y. Liu GNN AI4CE 95 32 0 14 May 2023
PAC-Bayesian Generalization Bounds for Adversarial Generative Models S. Mbacke Florence Clerc Pascal Germain 101 9 0 17 Feb 2023
Tighter Information-Theoretic Generalization Bounds from Supersamples Ziqiao Wang Yongyi Mao 109 19 0 05 Feb 2023
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization Sanae Lotfi Marc Finzi Sanyam Kapoor Andres Potapczynski Micah Goldblum A. Wilson BDL MLT AI4CE 87 62 0 24 Nov 2022
Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective Yige Yuan Bingbing Xu Huawei Shen Qi Cao Keting Cen Wen Zheng Xueqi Cheng 69 13 0 20 Nov 2022
A New Family of Generalization Bounds Using Samplewise Evaluated CMI Fredrik Hellström G. Durisi 92 26 0 12 Oct 2022
Information-Theoretic Analysis of Unsupervised Domain Adaptation Ziqiao Wang Yongyi Mao 119 11 0 03 Oct 2022
On Leave-One-Out Conditional Mutual Information For Generalization Mohamad Rida Rammal Alessandro Achille Aditya Golatkar Suhas Diggavi Stefano Soatto VLM 92 6 0 01 Jul 2022
Understanding Generalization via Leave-One-Out Conditional Mutual Information Mahdi Haghifam Shay Moran Daniel M. Roy Gintare Karolina Dziugaite 75 15 0 29 Jun 2022
Fisher SAM: Information Geometry and Sharpness Aware Minimisation Minyoung Kim Da Li S. Hu Timothy M. Hospedales AAML 87 72 0 10 Jun 2022
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees Haotian Ju Dongyue Li Hongyang R. Zhang 120 30 0 06 Jun 2022
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior Jun Yu Li Xu Luo Jian Li 72 4 0 27 May 2022
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms Romain Chor A. Gohari Gaël Richard Umut Simsekli 104 24 0 04 Mar 2022
Chained Generalisation Bounds Eugenio Clerico Amitis Shidani George Deligiannidis Arnaud Doucet AI4CE FedML 71 13 0 02 Mar 2022
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift Gholamali Aminian Mahed Abroshan Mohammad Mahdi Khalili Laura Toni M. Rodrigues OOD 114 28 0 24 Feb 2022
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks Pascal Esser L. C. Vankadara Debarghya Ghoshdastidar 69 56 0 07 Dec 2021
Towards a Unified Information-Theoretic Framework for Generalization Mahdi Haghifam Gintare Karolina Dziugaite Shay Moran Daniel M. Roy 150 34 0 09 Nov 2021
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm Yuheng Bu Gholamali Aminian Laura Toni Miguel R. D. Rodrigues G. Wornell 56 14 0 02 Nov 2021
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 67 76 0 28 Oct 2021
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives Zida Cheng Chuanwei Ruan Siheng Chen Sushant Kumar Ya Zhang 78 16 0 23 Oct 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 193 206 0 21 Oct 2021
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications Ziqiao Wang Yongyi Mao FedML MLT 124 26 0 07 Oct 2021
Information-theoretic generalization bounds for black-box learning algorithms Hrayr Harutyunyan Maxim Raginsky Greg Ver Steeg Aram Galstyan 136 44 0 04 Oct 2021
Information-Theoretic Characterization of the Generalization Error for Iterative Semi-Supervised Learning Haiyun He Hanshu Yan Vincent Y. F. Tan 97 11 0 03 Oct 2021
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis Qi Chen Changjian Shui M. Marchand 99 44 0 29 Sep 2021
PAC-Bayes Information Bottleneck Zifeng Wang Shao-Lun Huang E. Kuruoglu Jimeng Sun Xi Chen Yefeng Zheng 103 36 0 29 Sep 2021
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes Peter Grünwald Thomas Steinke Lydia Zakynthinou 78 30 0 17 Jun 2021
Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms Gholamali Aminian Laura Toni M. Rodrigues 139 16 0 03 Feb 2021
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent Gergely Neu Gintare Karolina Dziugaite Mahdi Haghifam Daniel M. Roy 117 90 0 01 Feb 2021
Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting Mengzhang Li Zhanxing Zhu GNN AI4TS 86 776 0 15 Dec 2020
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks Renjie Liao R. Urtasun R. Zemel 89 90 0 14 Dec 2020
Molecular graph generation with Graph Neural Networks P. Bongini Monica Bianchini F. Scarselli GNN 113 144 0 14 Dec 2020
Transfer Meta-Learning: Information-Theoretic Bounds and Information Meta-Risk Minimization Sharu Theresa Jose Osvaldo Simeone G. Durisi 114 17 0 04 Nov 2020
Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms Gholamali Aminian Laura Toni M. Rodrigues 76 31 0 23 Oct 2020
On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm Borja Rodríguez Gálvez Germán Bassi Ragnar Thobaben Mikael Skoglund 115 32 0 21 Oct 2020
Information-Theoretic Bounds on Transfer Generalization Gap Based on Jensen-Shannon Divergence Sharu Theresa Jose Osvaldo Simeone 106 16 0 13 Oct 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 205 1,360 0 03 Oct 2020
Tighter risk certificates for neural networks Maria Perez-Ortiz Omar Rivasplata John Shawe-Taylor Csaba Szepesvári UQCV 91 108 0 25 Jul 2020
Simple and Deep Graph Convolutional Networks Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding Yaliang Li GNN 147 1,507 0 04 Jul 2020
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks Kenta Oono Taiji Suzuki AI4CE 120 32 0 15 Jun 2020
Adaptive Universal Generalized PageRank Graph Neural Network Eli Chien Jianhao Peng Pan Li O. Milenkovic 294 747 0 14 Jun 2020
Information-theoretic analysis for transfer learning Xuetong Wu J. Manton U. Aickelin Jingge Zhu 51 34 0 18 May 2020
Generalization Bounds via Information Density and Conditional Information Density Fredrik Hellström G. Durisi 124 67 0 16 May 2020
Information-Theoretic Generalization Bounds for Meta-Learning and Applications Sharu Theresa Jose Osvaldo Simeone 76 47 0 09 May 2020
Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms Mahdi Haghifam Jeffrey Negrea Ashish Khisti Daniel M. Roy Gintare Karolina Dziugaite 206 108 0 27 Apr 2020