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NIPS
2001
14 years 11 months ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts
ECCV
2002
Springer
15 years 11 months ago
A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image...
Feng Han, Zhuowen Tu, Song Chun Zhu
UAI
2000
14 years 11 months ago
Minimum Message Length Clustering Using Gibbs Sampling
The K-Means and EM algorithms are popular in clustering and mixture modeling due to their simplicity and ease of implementation. However, they have several significant limitations...
Ian Davidson
ISBI
2006
IEEE
15 years 10 months ago
Coronary tree extraction from X-ray angiograms using marked point processes
In this paper, we use marked point processes to perform an unsupervised extraction of the coronary tree from 2D X-ray angiography. These processes provide a rigorous framework bas...
Caroline Lacoste, Gérard Finet, Isabelle E....
NIPS
2008
14 years 11 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray