Triplet Markov Chains Based- Estimation of Nonstationary Latent Variables Hidden with Independent Noise.
Mohamed El Yazid BoudarenEmmanuel MonfriniKadda Beghdad BeyAhmed HabbouchiWojciech PieczynskiPublished in: ICEIS (Revised Selected Papers) (2017)
Keyphrases
- non stationary
- latent variables
- markov chain
- markov processes
- steady state
- random fields
- probabilistic model
- markov fields
- finite state
- random variables
- transition probabilities
- posterior distribution
- topic models
- observed variables
- random walk
- prior knowledge
- gaussian process
- stochastic process
- markov model
- approximate inference
- hidden variables
- state space
- latent variable models
- instantaneous frequency
- parameter estimation
- probabilistic automata
- noise level
- stationary distribution
- autoregressive
- missing data
- markov chain monte carlo
- transition matrix
- gibbs sampling
- gaussian markov random fields
- structured prediction
- latent dirichlet allocation
- graphical models
- markov random field
- image segmentation
- machine learning