2017-07-17-chen17c.md

title	booktitle	year	volume	series	address	month	publisher	pdf	url	abstract	layout	id	tex_title	bibtex_author	firstpage	lastpage	page	order	cycles	editor	author	date	container-title	genre	issued	extras
Dueling Bandits with Weak Regret	Proceedings of the 34th International Conference on Machine Learning	2017	70	Proceedings of Machine Learning Research		0	PMLR	http://proceedings.mlr.press/v70/chen17c/chen17c.pdf	http://proceedings.mlr.press/v70/chen17c.html	We consider online content recommendation with implicit feedback through pairwise comparisons, formalized as the so-called dueling bandit problem. We study the dueling bandit problem in the Condorcet winner setting, and consider two notions of regret: the more well-studied strong regret, which is 0 only when both arms pulled are the Condorcet winner; and the less well-studied weak regret, which is 0 if either arm pulled is the Condorcet winner. We propose a new algorithm for this problem, Winner Stays (WS), with variations for each kind of regret: WS for weak regret (WS-W) has expected cumulative weak regret that is $O(N^2)$, and $O(N\log(N))$ if arms have a total order; WS for strong regret (WS-S) has expected cumulative strong regret of $O(N^2 + N \log(T))$, and $O(N\log(N)+N\log(T))$ if arms have a total order. WS-W is the first dueling bandit algorithm with weak regret that is constant in time. WS is simple to compute, even for problems with many arms, and we demonstrate through numerical experiments on simulated and real data that WS has significantly smaller regret than existing algorithms in both the weak- and strong-regret settings.	inproceedings	chen17c	Dueling Bandits with Weak Regret	Bangrui Chen and Peter I. Frazier	731	739	731-739	731	false	given family Doina Precup given family Yee Whye Teh	given family Bangrui Chen given family Peter I. Frazier	2017-07-17	Proceedings of the 34th International Conference on Machine Learning	inproceedings	date-parts 2017 7 17	label link Supplementary PDF http://proceedings.mlr.press/v70/chen17c/chen17c-supp.pdf