Large-Scale Methods for Distributionally Robust Optimization

12 October 2020

Papers citing "Large-Scale Methods for Distributionally Robust Optimization"

50 / 53 papers shown

Title
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws Xiyuan Wei Ming Lin Fanjiang Ye Fengguang Song Liangliang Cao My T. Thai Tianbao Yang LLMSV 34 0 0 10 May 2025
Nested Stochastic Gradient Descent for (Generalized) Sinkhorn Distance-Regularized Distributionally Robust Optimization Yuqing Yang Yi Zhou Zhaosong Lu 49 0 0 29 Mar 2025
Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Primal-Dual Balancing and Iteration Complexity Analysis Jiajin Li Lingling Zhu Anthony Man-Cho So 54 4 0 17 Jan 2025
Federated Learning with Relative Fairness Shogo H. Nakakita Tatsuya Kaneko Shinya Takamaeda-Yamazaki Masaaki Imaizumi FedML 32 2 0 02 Nov 2024
SOREL: A Stochastic Algorithm for Spectral Risks Minimization Yuze Ge Rujun Jiang 38 0 0 19 Jul 2024
Spuriousness-Aware Meta-Learning for Learning Robust Classifiers Guangtao Zheng Wenqian Ye Aidong Zhang 54 0 0 15 Jun 2024
AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark Li Lin Santosh Xin Wang Shu Hu Shu Hu EGVM 81 11 0 02 Jun 2024
Fast Computation of Superquantile-Constrained Optimization Through Implicit Scenario Reduction Jake Roth Ying Cui 31 2 0 13 May 2024
Robust COVID-19 Detection in CT Images with CLIP Li Lin Yamini Sri Krubha Zhenhuan Yang Cheng Ren Thuc Duy Le Irene Amerini Xin Wang Shu Hu 37 10 0 13 Mar 2024
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift Benjamin Eyre Elliot Creager David Madras Antonio Torralba Katherine Heller OOD OODD 40 1 0 29 Dec 2023
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning Prashant Khanduri Chengyin Li Rafi Ibn Sultan Yao Qiang Joerg Kliewer Dongxiao Zhu 42 0 0 21 Nov 2023
On the Parallel Complexity of Multilevel Monte Carlo in Stochastic Gradient Descent Kei Ishikawa BDL 63 0 0 03 Oct 2023
Bias Amplification Enhances Minority Group Performance Gaotang Li Jiarui Liu Wei Hu 28 5 0 13 Sep 2023
Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization Ting Wu Rui Zheng Tao Gui Qi Zhang Xuanjing Huang 51 2 0 20 May 2023
Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments Quoc Tran-Dinh 35 7 0 30 Mar 2023
Distributionally Robust Optimization with Probabilistic Group Soumya Suvra Ghosal Yixuan Li OOD 13 7 0 10 Mar 2023
Data-Driven Distributionally Robust Optimal Control with State-Dependent Noise Rui Liu Guan-Yu Shi Pratap Tokekar 19 7 0 04 Mar 2023
DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule Maor Ivgi Oliver Hinder Y. Carmon ODL 28 57 0 08 Feb 2023
$Extragradient-Type Methods with $\mathcal{O} (1/k)$ Last-Iterate Convergence Rates for Co-Hypomonotone Inclusions$ Extragradient-Type Methods with $\mathcal{O} (1/k)$ Last-Iterate Convergence Rates for Co-Hypomonotone Inclusions Quoc Tran-Dinh 31 2 0 08 Feb 2023
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access A. Veldanda Ivan Brugere Sanghamitra Dutta Alan Mishler S. Garg 39 5 0 02 Feb 2023
Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity Shixiong Wang Haowei Wang Xinke Li Jean Honorio OOD 65 1 0 31 Jan 2023
Model Agnostic Sample Reweighting for Out-of-Distribution Learning Xiao Zhou Yong Lin Renjie Pi Weizhong Zhang Renzhe Xu Peng Cui Tong Zhang OODD 39 60 0 24 Jan 2023
Stochastic Optimization for Spectral Risk Measures Ronak R. Mehta Vincent Roulet Krishna Pillutla Lang Liu Zaïd Harchaoui 32 6 0 10 Dec 2022
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization Le‐Yu Chen Haishan Ye Luo Luo 68 5 0 05 Dec 2022
Learning Antidote Data to Individual Unfairness Peizhao Li Ethan Xia Hongfu Liu FedML FaML 24 9 0 29 Nov 2022
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation Josh Gardner Zoran Popovic Ludwig Schmidt OOD 34 22 0 23 Nov 2022
Outlier-Aware Training for Improving Group Accuracy Disparities Li-Kuang Chen Canasai Kruengkrai Junichi Yamagishi 29 0 0 27 Oct 2022
Distributed Distributionally Robust Optimization with Non-Convex Objectives Yang Jiao Kai Yang Dongjin Song 29 11 0 14 Oct 2022
MaskTune: Mitigating Spurious Correlations by Forcing to Explore Saeid Asgari Taghanaki Aliasghar Khani Fereshte Khani A. Gholami Linh-Tam Tran Ali Mahdavi-Amiri Ghassan Hamarneh AAML 43 45 0 30 Sep 2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup Zongbo Han Zhipeng Liang Fan Yang Liu Liu Lanqing Li Yatao Bian P. Zhao Bing Wu Changqing Zhang Jianhua Yao 56 34 0 19 Sep 2022
Learning from a Biased Sample Roshni Sahoo Lihua Lei Stefan Wager 27 17 0 05 Sep 2022
Calibrated Selective Classification Adam Fisch Tommi Jaakkola Regina Barzilay 29 16 0 25 Aug 2022
Rank-based Decomposable Losses in Machine Learning: A Survey Shu Hu Xin Wang Siwei Lyu 38 32 0 18 Jul 2022
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization Y. Carmon A. Jambulapati Yujia Jin Aaron Sidford 58 11 0 17 Jun 2022
Learning to Split for Automatic Bias Detection Yujia Bao Regina Barzilay 17 20 0 28 Apr 2022
Distributionally Robust Models with Parametric Likelihood Ratios Paul Michel Tatsunori Hashimoto Graham Neubig OOD 30 15 0 13 Apr 2022
Distributionally Robust Optimization via Ball Oracle Acceleration Y. Carmon Danielle Hausler 18 11 0 24 Mar 2022
Challenges and Strategies in Cross-Cultural NLP Daniel Hershcovich Stella Frank Heather Lent Miryam de Lhoneux Mostafa Abdou ... Ruixiang Cui Constanza Fierro Katerina Margatina Phillip Rust Anders Søgaard 43 164 0 18 Mar 2022
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee Dixian Zhu Gang Li Bokun Wang Xiaodong Wu Tianbao Yang 33 29 0 01 Mar 2022
Towards Group Robustness in the presence of Partial Group Labels Vishnu Suresh Lokhande Kihyuk Sohn Jinsung Yoon Madeleine Udell Chen-Yu Lee Tomas Pfister OOD 37 11 0 10 Jan 2022
BARACK: Partially Supervised Group Robustness With Guarantees N. Sohoni Maziar Sanjabi Nicolas Ballas Aditya Grover Shaoliang Nie Hamed Firooz Christopher Ré OOD 20 24 0 31 Dec 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 32 19 0 09 Nov 2021
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis Jikai Jin Samir Bhatt Haiyang Wang Liwei Wang 32 48 0 24 Oct 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 46 35 0 24 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 55 517 0 31 Aug 2021
Stochastic Bias-Reduced Gradient Methods Hilal Asi Y. Carmon A. Jambulapati Yujia Jin Aaron Sidford 24 29 0 17 Jun 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 28 7 0 16 Feb 2021
Achieving Efficiency in Black Box Simulation of Distribution Tails with Self-structuring Importance Samplers Anand Deo Karthyek Murthy 22 10 0 14 Feb 2021
Attentional-Biased Stochastic Gradient Descent Q. Qi Yi Tian Xu Rong Jin W. Yin Tianbao Yang ODL 31 12 0 13 Dec 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems N. Sohoni Jared A. Dunnmon Geoffrey Angus Albert Gu Christopher Ré 30 242 0 25 Nov 2020