On the KL-Divergence-based Robust Satisficing Model

17 August 2024

Papers citing "On the KL-Divergence-based Robust Satisficing Model"

24 / 24 papers shown

Title
Concentration Bounds for Discrete Distribution Estimation in KL Divergence C. Canonne Ziteng Sun A. Suresh 111 4 0 14 Feb 2023
RLSbench: Domain Adaptation Under Relaxed Label Shift Saurabh Garg Nick Erickson James Sharpnack Alexander J. Smola Sivaraman Balakrishnan Zachary Chase Lipton VLM 84 33 0 06 Feb 2023
Domain Adaptation under Open Set Label Shift Saurabh Garg Sivaraman Balakrishnan Zachary Chase Lipton OOD VLM 61 42 0 26 Jul 2022
Deep Long-Tailed Learning: A Survey Yifan Zhang Bingyi Kang Bryan Hooi Shuicheng Yan Jiashi Feng VLM 107 588 0 09 Oct 2021
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence Qi Qi Youzhi Luo Zhao Xu Shuiwang Ji Tianbao Yang 45 63 0 18 Apr 2021
Domain Generalization: A Survey Kaiyang Zhou Ziwei Liu Yu Qiao Tao Xiang Chen Change Loy OOD AI4CE 248 1,019 0 03 Mar 2021
Coping with Label Shift via Distributionally Robust Optimisation J.N. Zhang A. Menon Andreas Veit Srinadh Bhojanapalli Sanjiv Kumar S. Sra OOD 71 71 0 23 Oct 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 61 384 0 14 Oct 2020
Tilted Empirical Risk Minimization Tian Li Ahmad Beirami Maziar Sanjabi Virginia Smith 72 135 0 02 Jul 2020
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning Yifan Hu Siqi Zhang Xin Chen Niao He ODL 92 56 0 25 Feb 2020
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning Daniel Kuhn Peyman Mohajerin Esfahani Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh OOD 64 395 0 23 Aug 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 195 2,242 0 05 Jul 2019
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao Colin Wei Adrien Gaidon Nikos Arechiga Tengyu Ma 127 1,607 0 18 Jun 2019
Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization Yifan Hu Xin Chen Niao He 56 35 0 28 May 2019
Large-Scale Long-Tailed Recognition in an Open World Ziwei Liu Zhongqi Miao Xiaohang Zhan Jiayun Wang Boqing Gong Stella X. Yu 151 1,163 0 10 Apr 2019
Learning Models with Uniform Performance via Distributionally Robust Optimization John C. Duchi Hongseok Namkoong OOD 66 423 0 20 Oct 2018
Adaptive Cost-sensitive Online Classification P. Zhao Yifan Zhang Min-man Wu Guosheng Lin Mingkui Tan Junzhou Huang 41 64 0 06 Apr 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 149 1,431 0 24 Mar 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 64 1,356 0 16 Feb 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 827 11,943 0 09 Mar 2017
Variance-based regularization with convex objectives John C. Duchi Hongseok Namkoong 76 351 0 08 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 122 1,775 0 19 Sep 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014
Rényi Divergence and Kullback-Leibler Divergence T. Erven P. Harremoes 87 1,341 0 12 Jun 2012