We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
A flow is said to be confluent if at any node all the flow leaves along a single edge. Given a directed graph G with k sinks and non-negative demands on all the nodes of G, we con...
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
This paper deals with the reconstruction of smooth, flexible, isometrically embedded flat surfaces in 3D, such as a sheet of paper or a flag waving in the wind, from a set of 2...
In a reverberant scenario, phase transformed weighted algorithms are more robust than Maximum Likelihood (ML) because of the insufficiency of the data model to incorporate reverb...