Machine Learning · Computer Science
Pure Exploration in Bandits with Linear Constraints
Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt Dubhashi
2024-01-26
Machine Learning · Computer Science
Minimax Optimal Algorithms for Adversarial Bandit Problem with Multiple Plays
N. Mert Vural, Hakan Gokcesu, Kaan Gokcesu, Suleyman S. Kozat
2019-12-02
Statistics Theory · Mathematics
Refined bounds for randomized experimental design
Geovani Rizk, Igor Colin, Albert Thomas, Moez Draief
2021-01-01
Machine Learning · Computer Science
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits
Julian Katz-Samuels, Lalit Jain, Zohar Karnin, Kevin Jamieson
2020-06-23
Machine Learning · Computer Science
Active Learning with Safety Constraints
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain +1
2022-06-23
Information Theory · Computer Science
Sequential Multi-hypothesis Testing in Multi-armed Bandit Problems:An Approach for Asymptotic Optimality
Gayathri R Prabhu, Srikrishna Bhashyam, Aditya Gopalan, Rajesh Sundaresan
2022-06-13
Machine Learning · Computer Science
Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits
Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos +2
2015-07-17
Machine Learning · Computer Science
Threshold-Based Optimal Arm Selection in Monotonic Bandits: Regret Lower Bounds and Algorithms
Chanakya Varude, Jay Chaudhary, Siddharth Kaushik, Prasanna Chaporkar
2025-09-03
Statistics Theory · Mathematics
Demonstration Experiments
Guido Imbens, Lorenzo Masoero, Alexander Rakhlin, Thomas S. Richardson +1
2026-03-10
Machine Learning · Computer Science
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget
Jasmin Brandt, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
2022-10-17