We consider decentralized control of Markov decision processes and give complexity bounds on the worst-case running time for algorithms that find optimal solutions. Generalization...
Daniel S. Bernstein, Shlomo Zilberstein, Neil Imme...
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Mixed-drove spatiotemporal co-occurrence patterns (MDCOPs) represent subsets of two or more different object-types whose instances are often located in spatial and temporal proximi...
Mete Celik, Shashi Shekhar, James P. Rogers, James...
Abstract--This paper offers a new technique for spatially adaptive estimation. The local likelihood is exploited for nonparametric modeling of observations and estimated signals. T...
We obtain the strongest separation between quantum and classical query complexity known to date--specifically, we define a black-box problem that requires exponentially many querie...