Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...
We present an algorithm to solve the sensor planning problem for a trinocular, active vision system. This algorithm uses an iterative optimization method to rst solve for the tran...
Solution of large sparse linear fixed-point problems lies at the heart of many important performance analysis calculations. These calculations include steady-state, transient and...
— Clustering is grouping of patterns according to similarity or distance in different perspectives. Various data representations, similarity measurements and organization manners...