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2010.07346
Cited By
Online Learning with Vector Costs and Bandits with Knapsacks
14 October 2020
Thomas Kesselheim
Sahil Singla
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Papers citing
"Online Learning with Vector Costs and Bandits with Knapsacks"
8 / 8 papers shown
Title
A New Benchmark for Online Learning with Budget-Balancing Constraints
M. Braverman
Jingyi Liu
Jieming Mao
Jon Schneider
Eric Xue
60
0
0
19 Mar 2025
Dataset Representativeness and Downstream Task Fairness
Victor A. Borza
Andrew Estornell
Chien-Ju Ho
Bradley Malin
Yevgeniy Vorobeychik
35
0
0
28 Jun 2024
Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints
Martino Bernasconi
Matteo Castiglioni
A. Celli
Federico Fusco
31
2
0
25 May 2024
No-Regret Algorithms in non-Truthful Auctions with Budget and ROI Constraints
Gagan Aggarwal
Giannis Fikioris
Mingfei Zhao
40
5
0
15 Apr 2024
Allocating Divisible Resources on Arms with Unknown and Random Rewards
Ningyuan Chen
Wenhao Li
24
0
0
28 Jun 2023
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications
Daniel Lee
Georgy Noarov
Mallesh M. Pai
Aaron Roth
27
13
0
09 Aug 2021
The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li
Chunlin Sun
Yinyu Ye
14
21
0
12 Feb 2021
Blackwell Approachability and Low-Regret Learning are Equivalent
Jacob D. Abernethy
Peter L. Bartlett
Elad Hazan
86
117
0
08 Nov 2010
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