106 citations · 636 across the 106 of their papers we have counts for
37 papers · 1 filter
Switchback Price Experiments with Forward-Looking Demand
Yifan Wu, Ramesh Johari, Vasilis Syrgkanis +1
Switchback experiments are widely used in pricing applications. We consider a retailer running such an experiment for the price of a single product, with infinite supply. In each p…
Bid Prediction in Repeated Auctions with Learning
Gali Noti, Vasilis Syrgkanis
We consider the problem of bid prediction in repeated auctions and evaluate the performance of econometric methods for learning agents using a dataset from a mainstream sponsored s…
Multi-item Non-truthful Auctions Achieve Good Revenue
Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier +2
We present a general framework for designing approximately revenue-optimal mechanisms for multi-item additive auctions, which applies to both truthful and non-truthful auctions. Gi…
Combinatorial Assortment Optimization
Nicole Immorlica, Brendan Lucier, Jieming Mao +2
Assortment optimization refers to the problem of designing a slate of products to offer potential customers, such as stocking the shelves in a convenience store. The price of each…
Learning to Bid Without Knowing your Value
Zhe Feng, Chara Podimata, Vasilis Syrgkanis
We address online learning in complex auction settings, such as sponsored search auctions, where the value of the bidder is unknown to her, evolving in an arbitrary manner and obse…
Optimal Data Acquisition for Statistical Estimation
Yiling Chen, Nicole Immorlica, Brendan Lucier +2
We consider a data analyst's problem of purchasing data from strategic agents to compute an unbiased estimate of a statistic of interest. Agents incur private costs to reveal their…
A Sample Complexity Measure with Applications to Learning Optimal Auctions
Vasilis Syrgkanis
We introduce a new sample complexity measure, which we refer to as split-sample growth rate. For any hypothesis and for any sample of size , the split-sample growth rate…
Optimal and Myopic Information Acquisition
Annie Liang, Xiaosheng Mu, Vasilis Syrgkanis
We consider the problem of optimal dynamic information acquisition from many correlated information sources. Each period, the decision-maker jointly takes an action and allocates a…
Simple vs Optimal Mechanisms in Auctions with Convex Payments
Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
We investigate approximately optimal mechanisms in settings where bidders' utility functions are non-linear; specifically, convex, with respect to payments (such settings arise, fo…
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…
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…
Truthful Multi-Parameter Auctions with Online Supply: an Impossible Combination
Nikhil R. Devanur, Balasubramanian Sivan, Vasilis Syrgkanis
We study a basic auction design problem with online supply. There are two unit-demand bidders and two types of items. The first item type will arrive first for sure, and the second…
Learning in Auctions: Regret is Hard, Envy is Easy
Constantinos Daskalakis, Vasilis Syrgkanis
A line of recent work provides welfare guarantees of simple combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) (Christodoulou et…
Pricing Queries Approximately Optimally
Vasilis Syrgkanis, Johannes Gehrke
Data as a commodity has always been purchased and sold. Recently, web services that are data marketplaces have emerged that match data buyers with data sellers. So far there are no…
No-Regret Learning in Bayesian Games
Jason Hartline, Vasilis Syrgkanis, Eva Tardos
Recent price-of-anarchy analyses of games of complete information suggest that coarse correlated equilibria, which characterize outcomes resulting from no-regret learning dynamics,…
Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo +1
We show that natural classes of regularized learning algorithms with a form of recency bias achieve faster convergence rates to approximate efficiency and to coarse correlated equi…
Econometrics for Learning Agents
Denis Nekipelov, Vasilis Syrgkanis, Eva Tardos
The main goal of this paper is to develop a theory of inference of player valuations from observed data in the generalized second price auction without relying on the Nash equilibr…
Efficiency Guarantees from Data
Darrell Hoy, Denis Nekipelov, Vasilis Syrgkanis
Analysis of efficiency of outcomes in game theoretic settings has been a main item of study at the intersection of economics and computer science. The notion of the price of anarch…
Learning and Efficiency in Games with Dynamic Population
Thodoris Lykouris, Vasilis Syrgkanis, Eva Tardos
We study the quality of outcomes in repeated games when the population of players is dynamically changing and participants use learning algorithms to adapt to the changing environm…
The Price of Anarchy in Large Games
Michal Feldman, Nicole Immorlica, Brendan Lucier +2
Game-theoretic models relevant for computer science applications usually feature a large number of players. The goal of this paper is to develop an analytical framework for boundin…
Greedy Algorithms make Efficient Mechanisms
Brendan Lucier, Vasilis Syrgkanis
We study mechanisms that use greedy allocation rules and pay-your-bid pricing to allocate resources subject to a matroid constraint. We show that all such mechanisms obtain a const…
Price of Stability in Games of Incomplete Information
Vasilis Syrgkanis
We address the question of whether price of stability results (existence of equilibria with low social cost) are robust to incomplete information. We show that this is the case in…
Bayesian Incentive-Compatible Bandit Exploration
Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis
Individual decision-makers consume information revealed by the previous decision makers, and produce information that may help in future decisions. This phenomenon is common in a w…