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Private and Communication-Efficient Algorithms for Entropy Estimation
For a joint distribution over many variables whose conditional independence is given by a tree, we describe algorithms for estimating Shannon entropy that require a number of samples that is linear in the number of variables, compared to the quadratic sample complexity of prior work.
Revenue Optimization in Posted-Price Auctions with Strategic Buyers
We study revenue optimization learning algorithms for posted-price auctions with strategic buyers.
Adaptation Algorithm and Theory Based on Generalized Discrepancy
We present a new algorithm for domain adaptation improving upon a discrepancy minimization algorithm previously shown to outperform a number of algorithms for this task.
Learning Theory and Algorithms for Revenue Optimization in Second-Price Auctions with Reserve
Second-price auctions with reserve play a critical role for modern search engine and popular online sites since the revenue of these companies often directly de- pends on the outcome of such auctions.
