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JMLR
2010
92views more  JMLR 2010»
13 years 12 days ago
Posterior distributions are computable from predictive distributions
As we devise more complicated prior distributions, will inference algorithms keep up? We highlight a negative result in computable probability theory by Ackerman, Freer, and Roy (...
Cameron E. Freer, Daniel M. Roy
CDC
2009
IEEE
150views Control Systems» more  CDC 2009»
13 years 10 months ago
Cooperative adaptive sampling via approximate entropy maximization
— This work deals with a group of mobile sensors sampling a spatiotemporal random field whose mean is unknown and covariance is known up to a scaling parameter. The Bayesian pos...
Rishi Graham, Jorge Cortés
NIPS
2003
13 years 7 months ago
Learning Bounds for a Generalized Family of Bayesian Posterior Distributions
In this paper we obtain convergence bounds for the concentration of Bayesian posterior distributions (around the true distribution) using a novel method that simplifies and enhan...
Tong Zhang
ICMCS
2008
IEEE
141views Multimedia» more  ICMCS 2008»
14 years 1 days ago
Visual focus of attention estimation from head pose posterior probability distributions
We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants from their head pose and contextual cues. The main contribution of the paper is ...
Sileye O. Ba, Jean-Marc Odobez
NIPS
2007
13 years 7 months ago
Predictive Matrix-Variate t Models
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
Shenghuo Zhu, Kai Yu, Yihong Gong