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NIPS
1998
13 years 9 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
ICML
2007
IEEE
14 years 9 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
MT
2002
107views more  MT 2002»
13 years 7 months ago
Translation with Scarce Bilingual Resources
Machine translation of human languages is a field almost as old as computers themselves. Recent approaches to this challenging problem aim at learning translation knowledge automat...
Yaser Al-Onaizan, Ulrich Germann, Ulf Hermjakob, K...
TC
2002
13 years 7 months ago
Dynamic Power Management for Nonstationary Service Requests
Dynamic Power Management (DPM) is a design methodology aiming at reducing power consumption of electronic systems by performing selective shutdown of idle system resources. The eff...
Eui-Young Chung, Luca Benini, Alessandro Bogliolo,...
ER
2010
Springer
114views Database» more  ER 2010»
13 years 6 months ago
KBB: A Knowledge-Bundle Builder for Research Studies
Researchers struggle to manage vast amounts of data coming from hundreds of sources in online repositories. To successfully conduct research studies, researchers need to find, ret...
David W. Embley, Stephen W. Liddle, Deryle W. Lons...