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 present smooth interpretation, a method to systematically approximate numerical imperative programs by smooth mathematical functions. This approximation facilitates the use of ...
Computing a minimum vertex cover in graphs and hypergraphs is a well-studied optimizaton problem. While intractable in general, it is well known that on bipartite graphs, vertex c...
Abstract—We study a network model in which each network link is associated with a set of delays and costs. These costs are a function of the delays and reflect the prices paid i...
: The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, has received increasing a...