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IROS
2007
IEEE
157views Robotics» more  IROS 2007»
15 years 9 months ago
Autonomous blimp control using model-free reinforcement learning in a continuous state and action space
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
Axel Rottmann, Christian Plagemann, Peter Hilgers,...
NIPS
1998
15 years 4 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
139
Voted
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
15 years 1 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
145
Voted
ICML
2007
IEEE
16 years 4 months ago
Reinforcement learning by reward-weighted regression for operational space control
Many robot control problems of practical importance, including operational space control, can be reformulated as immediate reward reinforcement learning problems. However, few of ...
Jan Peters, Stefan Schaal
ETS
2000
IEEE
156views Hardware» more  ETS 2000»
15 years 3 months ago
Parallel On-Line and In-Class Sections of "Writing for the Professions": A Practical Experiment
This paper describes experiences with on-line and in-class sections of a writing-intensive course, including a collaborative library literacy unit. It reports on a mid-semester so...
Victoria Hay, Dennis Isbell