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ESANN
2008
15 years 5 months ago
Similarities and differences between policy gradient methods and evolution strategies
Natural policy gradient methods and the covariance matrix adaptation evolution strategy, two variable metric methods proposed for solving reinforcement learning tasks, are contrast...
Verena Heidrich-Meisner, Christian Igel
JIRS
2010
120views more  JIRS 2010»
15 years 2 months ago
Designing Decentralized Controllers for Distributed-Air-Jet MEMS-Based Micromanipulators by Reinforcement Learning
Distributed-air-jet MEMS-based systems have been proposed to manipulate small parts with high velocities and without any friction problems. The control of such distributed systems ...
Laëtitia Matignon, Guillaume J. Laurent, Nadi...
ICDM
2009
IEEE
92views Data Mining» more  ICDM 2009»
15 years 1 months ago
Semi-supervised Multi-task Learning with Task Regularizations
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
Fei Wang, Xin Wang, Tao Li
PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
14 years 6 months ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang
KES
2007
Springer
15 years 10 months ago
Inductive Concept Retrieval and Query Answering with Semantic Knowledge Bases Through Kernel Methods
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Nicola Fanizzi, Claudia d'Amato