: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Interpretation interpretation is a theory of effective abstraction and/or approximation of discrete mathematical structures as found in the semantics of programming languages, mod...
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
We study the maximum edge-disjoint paths problem in undirected planar graphs: given a graph G and node pairs s1t1, s2t2, . . ., sktk, the goal is to maximize the number of pairs t...
Chandra Chekuri, Sanjeev Khanna, F. Bruce Shepherd
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...