90 search results - page 13 / 18 » Bayesian Inverse Reinforcement Learning |
NIPS
2008
13 years 9 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
TSP
2010
13 years 2 months ago
2010
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
ICRA
2008
IEEE
14 years 2 months ago
2008
IEEE
— In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera. O...
UAI
2008
13 years 9 months ago
2008
A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown p...