This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Embedded services and applications that interact with the real world often, over time, need to run on different kinds of hardware (low-cost microcontrollers to powerful multicore ...
Abstract. Data mining, which aims at extracting interesting information from large collections of data, has been widely used as an effective decision making tool. Mining the datas...