activity
20122023
most citedSize versus truthfulness in the House Allocation problem

12 citations · 26 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2023

Near-Optimal Experimental Design Under the Budget Constraint in Online Platforms

Yongkang Guo, Yuan Yuan, Jinshan Zhang +3

A/B testing, or controlled experiments, is the gold standard approach to causally compare the performance of algorithms on online platforms. However, conventional Bernoulli randomi…

cs.GT2022

No-regret Learning in Repeated First-Price Auctions with Budget Constraints

Rui Ai, Chang Wang, Chenchen Li +3

Recently the online advertising market has exhibited a gradual shift from second-price auctions to first-price auctions. Although there has been a line of works concerning online b…

cs.GT2015★ 1 cited

Social Welfare in One-Sided Matching Mechanisms

George Christodoulou, Aris Filos-Ratsikas, Soren Kristoffer Stiil Frederiksen +3

We study the Price of Anarchy of mechanisms for the well-known problem of one-sided matching, or house allocation, with respect to the social welfare objective. We consider both or…

cs.GT2014★ 12 cited

Size versus truthfulness in the House Allocation problem

Piotr Krysta, David Manlove, Baharak Rastegari +1

We study the House Allocation problem (also known as the Assignment problem), i.e., the problem of allocating a set of objects among a set of agents, where each agent has ordinal p…

cs.GT2013★ 7 cited

Pricing Ad Slots with Consecutive Multi-unit Demand

Xiaotie Deng, Paul Goldberg, Yang Sun +2

We consider the optimal pricing problem for a model of the rich media advertisement market, as well as other related applications. In this market, there are multiple buyers (advert…

cs.GT2012★ 6 cited

On Revenue Maximization with Sharp Multi-Unit Demands

Ning Chen, Xiaotie Deng, Paul. W. Goldberg +1

We consider markets consisting of a set of indivisible items, and buyers that have {\em sharp} multi-unit demand. This means that each buyer wants a specific number of it…