Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hy...
Jon Lee, Vahab S. Mirrokni, Viswanath Nagarajan, M...
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
We consider graph coloring problems where the cost of a coloring is the sum of the costs of the colors, and the cost of a color is a monotone concave function of the total weight ...
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...
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...