We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
This paper presents an innovative partitionbased time join strategy for temporal databases where time is represented by time intervals. The proposed method maps time intervals to ...
Navigation in computer generated information spaces may be difficult, resulting in users getting “lost in hyperspace.” This work aims to build on research from the area of ci...
Embedding algorithms are a method for revealing low dimensional structure in complex data. Most embedding algorithms are designed to handle objects of a single type for which pair...
Amir Globerson, Gal Chechik, Fernando Pereira, Naf...
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...