Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
In this contribution we present the dialogue generator module of a Dialogue-based Interactive Diagnostic and Learning System (DIDLS) for Historical Text Comprehension (HTC). The d...
Grammatiki Tsaganou, Maria Grigoriadou, Theodora C...
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
Utility computing delivers compute and storage resources to applications as an `on-demand utility', much like electricity, from a distributed collection of computing resource...
We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal ...
Peng Zang, Peng Zhou, David Minnen, Charles Lee Is...