This work studies the problem of distributed classification in peer-to-peer (P2P) networks. While there has been a significant amount of work in distributed classification, most o...
This paper takes a computational learning theory approach to a problem of linear systems identification. It is assumed that inputs are generated randomly from a known class consist...
Abstract. While a variety of multiple classifier systems have been studied since at least the late 1950's, this area came alive in the 90's with significant theoretical a...
In this paper, we present a novel method for human action recognition with the combined global movement feature and local configuration feature. The human action is represented as...
Abstract. We present a machine learning approach for classifying sentences as one-liner jokes or normal sentences. We use no deep analysis of the meaning to try to see if it is hum...