Online Linear Programming: Dual Convergence, New Algorithms, and Regret
Bounds

Online Linear Programming: Dual Convergence, New Algorithms, and Regret Bounds

12 September 2019

Xiaocheng Li

Papers citing "Online Linear Programming: Dual Convergence, New Algorithms, and Regret Bounds"

8 / 8 papers shown

Title
Learning to Price with Resource Constraints: From Full Information to Machine-Learned Prices Ruicheng Ao Jiashuo Jiang D. Simchi-Levi 60 1 0 24 Jan 2025
$Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods$ Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods Wenzhi Gao Chunlin Sun Chenyu Xue Dongdong Ge Yinyu Ye 59 1 0 08 Jan 2025
Degeneracy is OK: Logarithmic Regret for Network Revenue Management with Indiscrete Distributions Jiashuo Jiang Will Ma Jiawei Zhang 21 13 0 03 Jan 2025
Infrequent Resolving Algorithm for Online Linear Programming Guokai Li Yuan Wang Mingjie Li 26 1 0 01 Aug 2024
Trading-off price for data quality to achieve fair online allocation M. Molina Nicolas Gast P. Loiseau Vianney Perchet 24 4 0 23 Jun 2023
Online Contextual Decision-Making with a Smart Predict-then-Optimize Method Heyuan Liu Paul Grigas 16 8 0 15 Jun 2022
Fairer LP-based Online Allocation via Analytic Center Guanting Chen Xiaocheng Li Yinyu Ye FaML 16 8 0 27 Oct 2021
The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems S. Balseiro Haihao Lu Vahab Mirrokni 19 101 0 18 Nov 2020