We consider the problem of how the CNS learns to control dynamics of a mechanical system. By using a paradigm where a subject's hand interacts with a virtual mechanical envir...
A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful ...
Michael J. Pazzani, Subramani Mani, William Rodman...
In an interactive embedded system, special task execution patterns and scheduling constraints exist due to frequent human-computer interactions. This paper proposes a transaction-...
The analysis of network traces often requires to find the spots where something interesting happens. Since traces are usually very large data-sets, it is often not easy and time i...
This paper describes how computer-human interaction in ambient computing environments can be best informed by conceptualizing of such environments as problem solving systems. Typi...