Abstract— Research on numerical solution methods for partially observable Markov decision processes (POMDPs) has primarily focused on discrete-state models, and these algorithms ...
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
A strand is a sequence of events; it represents either the execution of legitimate party in a security protocol or else a sequence of actions by a penetrator. A strand space is a ...
F. Javier Thayer, Jonathan C. Herzog, Joshua D. Gu...
We describe a new randomized data structure, the sparse partition, for solving the dynamic closest-pair problem. Using this data structure the closest pair of a set of n points in ...
Mordecai J. Golin, Rajeev Raman, Christian Schwarz...
Skew is prevalent in data streams, and should be taken into account by algorithms that analyze the data. The problem of finding "biased quantiles"-- that is, approximate...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...