90 search results - page 13 / 18 » Bayesian Inverse Reinforcement Learning |
161
Voted
NIPS
2008
15 years 7 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...
168
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ATAL
2010
Springer
15 years 6 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...
184
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TSP
2010
15 years 15 days 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...
171
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ICRA
2008
IEEE
16 years 7 days 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...
179
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UAI
2008
15 years 7 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...