276 search results - page 27 / 56 » PAC-Learning of Markov Models with Hidden State |
IDEAL
2004
Springer
14 years 1 months ago
2004
Springer
We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
ICML
2001
IEEE
14 years 9 months ago
2001
IEEE
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
CVPR
1999
IEEE
14 years 10 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
GFKL
2007
Springer
14 years 2 months ago
2007
Springer
Abstract. Artificial systems with a high degree of autonomy require reliable semantic information about the context they operate in. State interpretation, however, is a difficult ...
ICASSP
2009
IEEE
14 years 3 months ago
2009
IEEE
Semi-continuous acoustic models, where the output distributions for all Hidden Markov Model states share a common codebook of Gaussian density functions, are a well-known and prov...