Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
One of the central problems in cognitive science is determining the mental representations that underlie human inferences. Solutions to this problem often rely on the analysis of ...
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
A novel measure for automatically quantifying the amount of interpersonal influence present in face-toface conversations is proposed based on the visualattention patterns of the p...
In situations where Bayesian networks (BN) inferencing approximation is allowable, we show how to reduce the amount of sensory observations necessary and in a multi-agent context ...