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UAI
2003
15 years 7 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
ICML
2010
IEEE
15 years 7 months ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh
CSDA
2010
165views more  CSDA 2010»
15 years 6 months ago
A two-component Weibull mixture to model early and late mortality in a Bayesian framework
A two component parametric mixture is proposed to model survival after an invasive treatment, when patients may experience different hazards regimes: a risk of early mortality dir...
Alessio Farcomeni, Alessandra Nardi
COGSCI
2006
75views more  COGSCI 2006»
15 years 6 months ago
A Hierarchical Bayesian Model of Human Decision-Making on an Optimal Stopping Problem
We consider human performance on an optimal stopping problem where people are presented with a list of numbers independently chosen from a uniform distribution. People are told ho...
Michael D. Lee
VLSISP
2002
123views more  VLSISP 2002»
15 years 6 months ago
Monte Carlo Bayesian Signal Processing for Wireless Communications
Abstract. Many statistical signal processing problems found in wireless communications involves making inference about the transmitted information data based on the received signal...
Xiaodong Wang, Rong Chen, Jun S. Liu