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Stochastic Constrained DRO with a Complexity Independent of Sample Size

11 October 2022

Papers citing "Stochastic Constrained DRO with a Complexity Independent of Sample Size"

34 / 34 papers shown

Title
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization Zimeng Qiu Quanqi Hu Zhuoning Yuan Denny Zhou Lijun Zhang Tianbao Yang 79 21 0 19 May 2023
CyCLIP: Cyclic Contrastive Language-Image Pretraining Shashank Goel Hritik Bansal S. Bhatia Ryan Rossi Vishwa Vinay Aditya Grover CLIP VLM 258 140 0 28 May 2022
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance Zhuoning Yuan Yuexin Wu Zi-qi Qiu Xianzhi Du Lijun Zhang Denny Zhou Tianbao Yang 128 30 0 24 Feb 2022
On the Complexity of a Practical Primal-Dual Coordinate Method Ahmet Alacaoglu Volkan Cevher Stephen J. Wright 60 13 0 19 Jan 2022
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis Jikai Jin Samir Bhatt Haiyang Wang Liwei Wang 70 51 0 24 Oct 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 109 38 0 24 Sep 2021
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation Junnan Li Ramprasaath R. Selvaraju Akhilesh Deepak Gotmare Shafiq Joty Caiming Xiong Guosheng Lin FaML 221 1,972 0 16 Jul 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 967 29,810 0 26 Feb 2021
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums Chaobing Song Stephen J. Wright Jelena Diakonikolas 114 17 0 26 Feb 2021
Distributionally Robust Federated Averaging Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 53 142 0 25 Feb 2021
Optimal Algorithms for Convex Nested Stochastic Composite Optimization Zhe Zhang Guanghui Lan 72 30 0 19 Nov 2020
Large-Scale Methods for Distributionally Robust Optimization Daniel Levy Y. Carmon John C. Duchi Aaron Sidford 78 217 0 12 Oct 2020
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization Tianyi Chen Yuejiao Sun W. Yin 114 82 0 25 Aug 2020
Tilted Empirical Risk Minimization Tian Li Ahmad Beirami Maziar Sanjabi Virginia Smith 72 135 0 02 Jul 2020
An Online Method for A Class of Distributionally Robust Optimization with Non-Convex Objectives Qi Qi Zhishuai Guo Yi Tian Xu Rong Jin Tianbao Yang 85 47 0 17 Jun 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 375 18,859 0 13 Feb 2020
A Simple and Effective Framework for Pairwise Deep Metric Learning Qi Qi Yan Yan Xiaoyu Wang Tianbao Yang 102 26 0 24 Dec 2019
Lower Bounds for Non-Convex Stochastic Optimization Yossi Arjevani Y. Carmon John C. Duchi Dylan J. Foster Nathan Srebro Blake E. Woodworth 93 363 0 05 Dec 2019
Decoupling Representation and Classifier for Long-Tailed Recognition Bingyi Kang Saining Xie Marcus Rohrbach Zhicheng Yan Albert Gordo Jiashi Feng Yannis Kalantidis OODD 180 1,222 0 21 Oct 2019
A Stochastic Composite Gradient Method with Incremental Variance Reduction Junyu Zhang Lin Xiao 51 68 0 24 Jun 2019
Distributionally Robust Optimization and Generalization in Kernel Methods Matthew Staib Stefanie Jegelka 72 133 0 27 May 2019
Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky Francesco Orabona ODL 86 410 0 24 May 2019
$Stochastic Primal-Dual Algorithms with Faster Convergence than $O(1/\sqrt{T})$ for Problems without Bilinear Structure$ Stochastic Primal-Dual Algorithms with Faster Convergence than $O(1/\sqrt{T})$ for Problems without Bilinear Structure Yan Yan Yi Tian Xu Qihang Lin Lijun Zhang Tianbao Yang 67 35 0 23 Apr 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
Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization Yi Zhou Zhe Wang Kaiyi Ji Yingbin Liang Vahid Tarokh ODL 67 14 0 07 Feb 2019
Learning Models with Uniform Performance via Distributionally Robust Optimization John C. Duchi Hongseok Namkoong OOD 63 423 0 20 Oct 2018
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang 72 110 0 04 Oct 2018
Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach John C. Duchi Peter Glynn Hongseok Namkoong 106 323 0 11 Oct 2016
Variance-based regularization with convex objectives John C. Duchi Hongseok Namkoong 76 351 0 08 Oct 2016
Statistical Estimation of Composite Risk Functionals and Risk Optimization Problems Darinka Dentcheva S. Penev A. Ruszczynski 47 71 0 10 Apr 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 364 19,723 0 09 Mar 2015
Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions Mengdi Wang Ethan X. Fang Han Liu 96 264 0 14 Nov 2014
Convex Optimization in Julia Madeleine Udell Karanveer Mohan David Zeng Jenny Hong Steven Diamond Stephen P. Boyd 70 165 0 17 Oct 2014
Solving variational inequalities with Stochastic Mirror-Prox algorithm A. Juditsky A. Nemirovskii Claire Tauvel 140 444 0 04 Sep 2008