Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
Location information gathered from a variety of sources in the form of sensor data, video streams, human observations, and so on, is often imprecise and uncertain and needs to be ...
Dmitri V. Kalashnikov, Yiming Ma, Sharad Mehrotra,...
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...