Tighter Variational Representations of f-Divergences via Restriction to Probability Measures

18 June 2012

Papers citing "Tighter Variational Representations of f-Divergences via Restriction to Probability Measures"

35 / 35 papers shown

Title
Benchmarking Mutual Information-based Loss Functions in Federated Learning Sarang S Harsh D. Chothani Qilei Li A. Abdelmoniem Arnab K. Paul FedML 56 0 0 16 Apr 2025
Identifiability of a statistical model with two latent vectors: Importance of the dimensionality relation and application to graph embedding Hiroaki Sasaki CML 54 0 0 30 May 2024
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis Daniel Csillag C. Struchiner G. Goedert OOD CML 74 2 0 15 May 2024
Better-than-KL PAC-Bayes Bounds Ilja Kuzborskij Kwang-Sung Jun Yulian Wu Kyoungseok Jang Francesco Orabona FedML 84 2 0 14 Feb 2024
Addressing GAN Training Instabilities via Tunable Classification Losses Monica Welfert Gowtham R. Kurri Kyle Otstot Lalitha Sankar 67 13 0 27 Oct 2023
Understanding Contrastive Learning via Distributionally Robust Optimization Junkang Wu Jiawei Chen Jiancan Wu Wentao Shi Xiang Wang Xiangnan He 120 27 0 17 Oct 2023
Sample Complexity of Probability Divergences under Group Symmetry Ziyu Chen Markos A. Katsoulakis Luc Rey-Bellet Weixia Zhu 127 10 0 03 Feb 2023
Information Processing Equalities and the Information-Risk Bridge Robert C. Williamson Zac Cranko 70 5 0 25 Jul 2022
Outcome Assumptions and Duality Theory for Balancing Weights David Bruns-Smith Avi Feller 62 5 0 17 Mar 2022
From Generalisation Error to Transportation-cost Inequalities and Back A. Esposito Michael C. Gastpar 74 7 0 08 Feb 2022
Structure-preserving GANs Jeremiah Birrell Markos A. Katsoulakis Luc Rey-Bellet Wei-wei Zhu GAN 91 18 0 02 Feb 2022
Preserving Domain Private Representation via Mutual Information Maximization Jiahong Chen Jing Wang Weipeng Lin Kuangen Zhang Clarence W. de Silva OOD 37 4 0 09 Jan 2022
Estimating and Maximizing Mutual Information for Knowledge Distillation A. Shrivastava Yanjun Qi Vicente Ordonez 56 6 0 29 Oct 2021
Moreau-Yosida $f$ -divergences Dávid Terjék 68 6 0 26 Feb 2021
Regularized Policies are Reward Robust Hisham Husain K. Ciosek Ryota Tomioka 55 25 0 18 Jan 2021
Combating the Instability of Mutual Information-based Losses via Regularization Kwanghee Choi Siyeong Lee AAML 62 4 0 16 Nov 2020
$(f,Γ)$ -Divergences: Interpolating between $f$ -Divergences and Integral Probability Metrics Jeremiah Birrell P. Dupuis Markos A. Katsoulakis Yannis Pantazis Luc Rey-Bellet 71 8 0 11 Nov 2020
Multimodal Image-to-Image Translation via Mutual Information Estimation and Maximization Zhiwen Zuo Lei Zhao Zhizhong Wang Haibo Chen Ailin Li Qijiang Xu Wei Xing Dongming Lu GAN 91 0 0 08 Aug 2020
Variational Representations and Neural Network Estimation of Rényi Divergences Jeremiah Birrell P. Dupuis Markos A. Katsoulakis Luc Rey-Bellet Jie Wang 80 33 0 07 Jul 2020
On the Theoretical Equivalence of Several Trade-Off Curves Assessing Statistical Proximity Rodrigue Siry Ryan Webster Loïc Simon Julien Rabin 63 5 0 21 Jun 2020
Optimizing Variational Representations of Divergences and Accelerating their Statistical Estimation Jeremiah Birrell Markos A. Katsoulakis Yannis Pantazis 50 22 0 15 Jun 2020
Optimal Bounds between $f$ -Divergences and Integral Probability Metrics R. Agrawal Thibaut Horel 69 39 0 10 Jun 2020
Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation Yuki Ohnishi Jean Honorio 22 0 0 25 Feb 2020
Bridging the Gap Between $f$ -GANs and Wasserstein GANs Jiaming Song Stefano Ermon 105 40 0 22 Oct 2019
Sample Elicitation Jiaheng Wei Zuyue Fu Yang Liu Xingyu Li Zhuoran Yang Zhaoran Wang SyDa 217 0 0 08 Oct 2019
On Mutual Information Maximization for Representation Learning Michael Tschannen Josip Djolonga Paul Kishan Rubenstein Sylvain Gelly Mario Lucic SSL 196 502 0 31 Jul 2019
Deep Learning for Channel Coding via Neural Mutual Information Estimation Rick Fritschek Rafael F. Schaefer Gerhard Wunder 85 46 0 07 Mar 2019
Information Losses in Neural Classifiers from Sampling Brandon Foggo N. Yu Jie Shi Yuanqi Gao 32 7 0 15 Feb 2019
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning Casey Chu Jose H. Blanchet Peter Glynn GAN 75 26 0 30 Jan 2019
Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning Hao Zhu Huaibo Huang Yi Li Aihua Zheng Ran He CVBM 70 58 0 17 Dec 2018
The Inductive Bias of Restricted f-GANs Shuang Liu Kamalika Chaudhuri GAN 49 18 0 12 Sep 2018
Disentangling the independently controllable factors of variation by interacting with the world Valentin Thomas Emmanuel Bengio W. Fedus Jules Pondard Philippe Beaudoin Hugo Larochelle Joelle Pineau Doina Precup Yoshua Bengio DRL CoGe CML 65 62 0 26 Feb 2018
MINE: Mutual Information Neural Estimation Mohamed Ishmael Belghazi A. Baratin Sai Rajeswar Sherjil Ozair Yoshua Bengio Aaron Courville R. Devon Hjelm DRL 270 1,287 0 12 Jan 2018
Parametric Adversarial Divergences are Good Losses for Generative Modeling Gabriel Huang Hugo Berard Ahmed Touati Gauthier Gidel Pascal Vincent Simon Lacoste-Julien GAN 56 1 0 08 Aug 2017
Fairness-Aware Learning with Restriction of Universal Dependency using f-Divergences Kazuto Fukuchi Jun Sakuma FedML FaML 27 2 0 25 Jun 2015