In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
Relevant Component Analysis (RCA) has been proposed for learning distance metrics with contextual constraints for image retrieval. However, RCA has two important disadvantages. On...
Steven C. H. Hoi, Wei Liu, Michael R. Lyu, Wei-Yin...
Models of agent-environment interaction that use predictive state representations (PSRs) have mainly focused on the case of discrete observations and actions. The theory of discre...
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...