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» Learning to Solve QBF
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ICML
2001
IEEE
14 years 11 months ago
Expectation Maximization for Weakly Labeled Data
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
Yuri A. Ivanov, Bruce Blumberg, Alex Pentland
SIGCSE
2004
ACM
132views Education» more  SIGCSE 2004»
14 years 3 months ago
Using game days to teach a multiagent system class
Multiagent systems is an attractive problem solving approach that is becoming ever more feasible and popular in today’s world. It combines artificial intelligence (AI) and distr...
Leen-Kiat Soh
SARA
2007
Springer
14 years 4 months ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Anders Jonsson, Andrew G. Barto
ICANN
2005
Springer
14 years 3 months ago
Reinforcement Learning in MirrorBot
For this special session of EU projects in the area of NeuroIT, we will review the progress of the MirrorBot project with special emphasis on its relation to reinforcement learning...
Cornelius Weber, David Muse, Mark Elshaw, Stefan W...
CIS
2005
Springer
14 years 3 months ago
Two Adaptive Matching Learning Algorithms for Independent Component Analysis
Independent component analysis (ICA) has been applied in many fields of signal processing and many ICA learning algorithms have been proposed from different perspectives. However...
Jinwen Ma, Fei Ge, Dengpan Gao