240 citations · 931 across the 63 of their papers we have counts for
9 papers · 1 filter
Adversarial Bandits with Knapsacks
Nicole Immorlica, Karthik Abinav Sankararaman, Robert Schapire +1
We consider Bandits with Knapsacks (henceforth, BwK), a general model for multi-armed bandits under supply/budget constraints. In particular, a bandit algorithm needs to solve a we…
Multidimensional Dynamic Pricing for Welfare Maximization
Aaron Roth, Aleksandrs Slivkins, Jonathan Ullman +1
We study the problem of a seller dynamically pricing distinct types of indivisible goods, when faced with the online arrival of unit-demand buyers drawn independently from an u…
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
Crowdsourcing markets have emerged as a popular platform for matching available workers with tasks to complete. The payment for a particular task is typically set by the task's req…
Bandits and Experts in Metric Spaces
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
In a multi-armed bandit problem, an online algorithm chooses from a set of strategies in a sequence of trials so as to maximize the total payoff of the chosen strategies. While the…
Bandits with Knapsacks
Ashwinkumar Badanidiyuru, Robert Kleinberg, Aleksandrs Slivkins
Multi-armed bandit problems are the predominant theoretical model of exploration-exploitation tradeoffs in learning, and they have countless applications ranging from medical trial…
Sharp Dichotomies for Regret Minimization in Metric Spaces
Robert Kleinberg, Aleksandrs Slivkins
The Lipschitz multi-armed bandit (MAB) problem generalizes the classical multi-armed bandit problem by assuming one is given side information consisting of a priori upper bounds on…
Contextual Bandits with Similarity Information
Aleksandrs Slivkins
In a multi-armed bandit (MAB) problem, an online algorithm makes a sequence of choices. In each round it chooses from a time-invariant set of alternatives and receives the payoff a…
Characterizing Truthful Multi-Armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
We consider a multi-round auction setting motivated by pay-per-click auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which i…
Multi-Armed Bandits in Metric Spaces
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
In a multi-armed bandit problem, an online algorithm chooses from a set of strategies in a sequence of trials so as to maximize the total payoff of the chosen strategies. While the…