The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
This paper investigates the role of online resources in problem solving. We look specifically at how programmers--an exemplar form of knowledge workers--opportunistically interlea...
Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira ...
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...