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NIPS
2003
15 years 1 months ago
Gaussian Processes in Reinforcement Learning
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
Carl Edward Rasmussen, Malte Kuss
143
Voted
MLDM
2007
Springer
15 years 6 months ago
Mining Frequent Trajectories of Moving Objects for Location Prediction
Advances in wireless and mobile technology flood us with amounts of moving object data that preclude all means of manual data processing. The volume of data gathered from position...
Mikolaj Morzy
103
Voted
ICIP
2004
IEEE
16 years 2 months ago
Multi-label SVM active learning for image classification
Image classification is an important task in computer vision. However, how to assign suitable labels to images is a subjective matter, especially when some images can be categoriz...
Xuchun Li, Lei Wang, Eric Sung
89
Voted
ICLP
2010
Springer
15 years 4 months ago
Learning Domain-Specific Heuristics for Answer Set Solvers
In spite of the recent improvements in the performance of Answer Set Programming (ASP) solvers, when the search space is sufficiently large, it is still possible for the search al...
Marcello Balduccini
86
Voted
COLING
2008
15 years 2 months ago
Learning Reliable Information for Dependency Parsing Adaptation
In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...
Wenliang Chen, Youzheng Wu, Hitoshi Isahara