106 citations · 636 across the 106 of their papers we have counts for
6 papers · 1 filter
Oracle-Efficient Online Learning and Auction Design
Miroslav Dudík, Nika Haghtalab, Haipeng Luo +3
We consider the design of computationally efficient online learning algorithms in an adversarial setting in which the learner has access to an offline optimization oracle. We prese…
The Price of Anarchy in Auctions
Tim Roughgarden, Vasilis Syrgkanis, Eva Tardos
This survey outlines a general and modular theory for proving approximation guarantees for equilibria of auctions in complex settings. This theory complements traditional economic…
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits
Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy +1
We give an oracle-based algorithm for the adversarial contextual bandit problem, where either contexts are drawn i.i.d. or the sequence of contexts is known a priori, but where the…
Efficient Algorithms for Adversarial Contextual Learning
Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire
We provide the first oracle efficient sublinear regret algorithms for adversarial versions of the contextual bandit problem. In this problem, the learner repeatedly makes an action…
Bayesian Exploration: Incentivizing Exploration in Bayesian Games
Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis +1
We consider a ubiquitous scenario in the Internet economy when individual decision-makers (henceforth, agents) both produce and consume information as they make strategic choices i…
Optimal Auctions with Convex Perceived Payments
Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
Myerson derived a simple and elegant solution to the single-parameter revenue-maximization problem in his seminal work on optimal auction design assuming the usual model of quasi-l…