Utility elicitation is a critical function of any automated decision aid, allowing decisions to be tailored to the preferences of a specific user. However, the size and complexit...
Previous work on sensitivity analysis in Bayesian networks has focused on single parameters, where the goal is to understand the sensitivity of queries to single parameter changes...
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...
In this paper we describe a methodology that includes the complementary use of simulated annealing and response surface methodology (RSM). The methodology was developed for analys...
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan