Abstract. We consider the problem of approximating the average distance between pairs of points in a high-dimensional Euclidean space, and more generally in any metric space. We co...
Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
Belief propagation on cyclic graphs is an efficient algorithm for computing approximate marginal probability distributions over single nodes and neighboring nodes in the graph. I...
We introduce a facility location problem with submodular facility cost functions, and give an O(log n) approximation algorithm for it. Then we focus on a special case of submodula...
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...