We present the design and analysis of an approximately incentive-compatible combinatorial auction. In just a single run, the auction is able to extract enough value information fr...
We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0n...
Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
We consider the problem of query rewrites in the context of keyword advertisement. Given a three-layer graph consisting of queries, query rewrites, and the corresponding ads that ...
Azarakhsh Malekian, Chi-Chao Chang, Ravi Kumar, Gr...