Inverse Reinforcement Learning using Expectation Maximization in mixture models.
Jürgen T. HahnAbdelhak M. ZoubirPublished in: ICASSP (2015)
Keyphrases
- mixture model
- bayesian nonparametric
- expectation maximization
- em algorithm
- inverse reinforcement learning
- probabilistic model
- gaussian mixture model
- density estimation
- probability density function
- maximum likelihood
- unsupervised learning
- generative model
- parameter estimation
- image segmentation
- gaussian mixture
- finite mixture model
- model based clustering
- hierarchical dirichlet process
- variational inference
- k means
- mixture modeling
- dirichlet process
- language model
- maximum a posteriori
- bayesian framework
- preference elicitation
- finite mixtures
- exponential family
- reward function
- posterior distribution
- hyperparameters
- gaussian distribution
- model selection
- high dimensional
- pairwise
- bayesian networks
- finite mixture models
- feature selection
- information retrieval