We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Design pattern density is a metric that measures how much of an object-oriented design can be understood and represented as instances of design patterns. Expert developers have lo...
The user expectations for usability and personalization along with decreasing size of handheld devices challenge traditional keypad layout design. We have developed a method for o...