99 search results - page 4 / 20 » Learning Hidden Markov Models with Distributed State Represe... |
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
NIPS
2007
13 years 9 months ago
2007
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
IDEAL
2004
Springer
14 years 29 days 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
2010
IEEE
13 years 8 months ago
2010
IEEE
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
JMLR
2010
13 years 2 months ago
2010
Hsu et al. (2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their assumptions and prove a tighte...