112 search results - page 7 / 23 » Beam sampling for the infinite hidden Markov model |
CORR
2008
Springer
13 years 7 months ago
2008
Springer
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
CVPR
2004
IEEE
13 years 11 months ago
2004
IEEE
In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
NIPS
2001
13 years 8 months ago
2001
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
BMCBI
2007
13 years 7 months ago
2007
Background: Profile Hidden Markov Models (HMM) are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have b...
EMNLP
2009
13 years 5 months ago
2009
We extend previous work on fully unsupervised part-of-speech tagging. Using a non-parametric version of the HMM, called the infinite HMM (iHMM), we address the problem of choosing...