Results 1  10
of
2,529,615
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 the use of a head pose posterior distribution as a representation of the head pose information contained in the image dat ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
data. This posterior encodes the probabilities of the different head poses given the image data, and constitute therefore a richer representation of the data than the mean or the mode of this distribution, as done in all previous work. These observations are exploited in a joint interaction model
NEW ACCEPT/REJECT METHODS FOR INDEPENDENT SAMPLING FROM POSTERIOR PROBABILITY DISTRIBUTIONS
"... Rejection sampling (RS) is a wellknown method to generate (pseudo)random samples from arbitrary probability distributions that enjoys important applications, either by itself or as a tool in more sophisticated Monte Carlo techniques. Unfortunately, the use of RS techniques demands the calculation ..."
Abstract
 Add to MetaCart
Rejection sampling (RS) is a wellknown method to generate (pseudo)random samples from arbitrary probability distributions that enjoys important applications, either by itself or as a tool in more sophisticated Monte Carlo techniques. Unfortunately, the use of RS techniques demands the calculation
Visual Focus of Attention Estimation from Head Pose Posterior Probability Distributions
"... submitted for publication ..."
‘wIAKING BINARY D6CISIONS BASED ON THE POSTERIOR PROBABILITY DISTRIBUTION ASSOCIATED WITH TOMOGRAPHIC RECONSTRUCTIONS
"... ABSTRACT. An optimal solution to the problem of making binary dmisione about a local region of a reconstruction is prov; ded by the Bayeeian method. The decieion is made on the baia of the ratio of the poeterior probabilities for the two hypoth~. The full Bayeaian procedure mquiree an integration of ..."
Abstract
 Add to MetaCart
ABSTRACT. An optimal solution to the problem of making binary dmisione about a local region of a reconstruction is prov; ded by the Bayeeian method. The decieion is made on the baia of the ratio of the poeterior probabilities for the two hypoth~. The full Bayeaian procedure mquiree an integration
Bayesian Interpolation
 Neural Computation
, 1991
"... Although Bayesian analysis has been in use since Laplace, the Bayesian method of modelcomparison has only recently been developed in depth. In this paper, the Bayesian approach to regularisation and modelcomparison is demonstrated by studying the inference problem of interpolating noisy data. T ..."
Abstract

Cited by 721 (17 self)
 Add to MetaCart
. The concepts and methods described are quite general and can be applied to many other problems. Regularising constants are set by examining their posterior probability distribution. Alternative regularisers (priors) and alternative basis sets are objectively compared by evaluating the evidence for them
Markov chains for exploring posterior distributions
 Annals of Statistics
, 1994
"... Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at ..."
Abstract

Cited by 1122 (6 self)
 Add to MetaCart
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at
Evaluating the Accuracy of SamplingBased Approaches to the Calculation of Posterior Moments
 IN BAYESIAN STATISTICS
, 1992
"... Data augmentation and Gibbs sampling are two closely related, samplingbased approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accurac ..."
Abstract

Cited by 583 (14 self)
 Add to MetaCart
Data augmentation and Gibbs sampling are two closely related, samplingbased approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical
Approximating discrete probability distributions with dependence trees
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1968
"... A method is presented to approximate optimally an ndimensional discrete probability distribution by a product of secondorder distributions, or the distribution of the firstorder tree dependence. The problem is to find an optimum set of n1 first order dependence relationship among the n variables ..."
Abstract

Cited by 874 (0 self)
 Add to MetaCart
A method is presented to approximate optimally an ndimensional discrete probability distribution by a product of secondorder distributions, or the distribution of the firstorder tree dependence. The problem is to find an optimum set of n1 first order dependence relationship among the n
DISTRIBUTED SYSTEMS
, 1985
"... Growth of distributed systems has attained unstoppable momentum. If we better understood how to think about, analyze, and design distributed systems, we could direct their implementation with more confidence. ..."
Abstract

Cited by 755 (1 self)
 Add to MetaCart
Growth of distributed systems has attained unstoppable momentum. If we better understood how to think about, analyze, and design distributed systems, we could direct their implementation with more confidence.
Distributional Clustering Of English Words
 In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics
, 1993
"... We describe and evaluate experimentally a method for clustering words according to their dis tribution in particular syntactic contexts. Words are represented by the relative frequency distributions of contexts in which they appear, and relative entropy between those distributions is used as the si ..."
Abstract

Cited by 631 (30 self)
 Add to MetaCart
as the similarity measure for clustering. Clusters are represented by average context distributions derived from the given words according to their probabilities of cluster membership. In many cases, the clusters can be thought of as encoding coarse sense distinctions. Deterministic annealing is used to find lowest
Results 1  10
of
2,529,615