We propose an optimization algorithm to execute a previously unlearned task-oriented command in an intelligent machine. We show that a well-defined, physically bounded, task-orien...
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
Energy-efficient computing is important in several systems ranging from embedded devices to large scale data centers. Several application domains offer the opportunity to tradeof...
Alerting systems and related decision-making automation are widely used to enhance the safety and capability of controlled processes across many applications. Traditional alerting ...
In this paper, I will discuss a set of techniques for supporting limited variable binding in behavior-based systems. This adds additional useful expressivity while preserving the ...