RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
We propose an algorithm to increase the resolution of multispectral satellite images knowing the panchromatic image at high resolution and the spectral channels at lower resolutio...
Coloma Ballester, Vicent Caselles, Laura Igual, Jo...
In this paper we present a novel face classification system
where we represent face images as a spatial arrangement
of image patches, and seek a smooth non-linear functional
map...
In this work, we propose a new FPGA design flow that combines the CUDA programming model from Nvidia with the state of the art high-level synthesis tool AutoPilot from AutoESL, to...
Most research on QoS-aware computing considers systems where code is generally partitioned into separately schedulable tasks with associated timing constraints. In sharp contrast ...
Ronghua Zhang, Tarek F. Abdelzaher, John A. Stanko...