• Publications
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Locality-sensitive hashing scheme based on p-stable distributions
TLDR
We present a novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem under lp norm, based on p-stable distributions. Expand
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Correlation clustering in general weighted graphs
TLDR
We give an O(log n)-approximation algorithm for the general case based on a linear-programming rounding and the "region-growing" technique. Expand
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Matroids, secretary problems, and online mechanisms
TLDR
We study a generalization of the classical secretary problem which we call the "matroid secretary problem". Expand
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A Knapsack Secretary Problem with Applications
TLDR
We consider situations in which a decision-maker with a fixed budget faces a sequence of options, each with a cost and a value, and must select a subset of them online so as to maximize the total value. Expand
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A Simple and Approximately Optimal Mechanism for an Additive Buyer
TLDR
We consider a monopolist seller with n heterogeneous items, facing a single buyer. Expand
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Marriage, honesty, and stability
TLDR
We show that, with high probability, the truthful strategy is the best response for a given player when the other players are truthful. Expand
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Limitations of cross-monotonic cost sharing schemes
TLDR
A cost sharing scheme is a set of rules defining how to share the cost of a service (often computed by solving a combinatorial optimization problem) amongst serviced customers. Expand
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Semantic similarity between search engine queries using temporal correlation
TLDR
We investigate the idea of finding semantically related search engine queries based on their temporal correlation; in other words, we infer that two queries are related if their popularities behave similarly over time. Expand
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Coordination mechanisms for selfish scheduling
TLDR
We study coordination mechanisms for four classes of multiprocessor machine scheduling problems and derive upper and lower bounds on the price of anarchy of these mechanisms. Expand
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Dynamics of bid optimization in online advertisement auctions
TLDR
We consider the problem of online keyword advertising auctions among multiple bidders with limited budgets, and study a natural bidding heuristic in which advertisers attempt to optimize their utility by equalizing their return-on-investment across all keywords. Expand
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