V
Vahab Mirrokni
Researcher at Google
Publications - 390
Citations - 16175
Vahab Mirrokni is an academic researcher from Google. The author has contributed to research in topics: Computer science & Common value auction. The author has an hindex of 57, co-authored 346 publications receiving 14255 citations. Previous affiliations of Vahab Mirrokni include Vassar College & Microsoft.
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Journal ArticleDOI
Uncoordinated Two-Sided Matching Markets
TL;DR: An exponential lower bound for the convergence time of the random better response dynamics in two-sided markets is given and a cycle of best responses is presented and it is proved that the random best response dynamics converges to a stable matching with probability one, but its convergence time is exponential.
Journal ArticleDOI
Limitations of cross-monotonic cost-sharing schemes
TL;DR: This paper investigates the limitations imposed by the cross-monotonicity property on cost-sharing schemes for several combinatorial optimization games including edge cover, vertex cover, set cover, metric facility location, maximum flow, arborescence packing, and maximum matching, and develops a novel technique based on the probabilistic method for proving upper bounds on the budget-balance factor ofCross-monotonic cost sharing schemes.
Journal ArticleDOI
Ego-net community mining applied to friend suggestion
TL;DR: A new technique is designed to efficiently build and cluster all the ego-nets of a graph in parallel, and it is proved formally on a stylized model and by experimental analysis that this new similarity measure outperforms the classic local features employed for friend suggestions.
Proceedings ArticleDOI
Bid optimization for broad match ad auctions
TL;DR: These results are the first to address bid optimization under the broad match feature which is common in ad auctions and present a constant-factor approximation when the optimal profit significantly exceeds the cost.
Journal ArticleDOI
Decentralized Utilitarian Mechanisms for Scheduling Games
TL;DR: This work demonstrates local mechanisms that induce outcomes with social cost close to that of the socially optimal solution in the setting of a classic scheduling problem and finds that mechanisms yielding Pareto dominated outcomes may in fact enhance the overall performance of the system.