A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing a...
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data. The MISUS system combines techniques...
Tara A. Estlin, Daniel M. Gaines, Forest Fisher, R...
Knowledge transfer between expert and novice agents is a challenging problem given that the knowledge representation and learning algorithms used by the novice learner can be fund...