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» An Algorithm for Learning Abductive Rules
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UAI
1997
13 years 9 months ago
Update Rules for Parameter Estimation in Bayesian Networks
This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Eric Bauer, Daphne Koller, Yoram Singer
NIPS
2008
13 years 9 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
ISCAS
2003
IEEE
117views Hardware» more  ISCAS 2003»
14 years 1 months ago
Learning temporal correlations in biologically-inspired aVLSI
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Adria Bofill-i-Petit, Alan F. Murray
CVPR
2007
IEEE
14 years 2 months ago
Trajectory Series Analysis based Event Rule Induction for Visual Surveillance
In this paper, a generic rule induction framework based on trajectory series analysis is proposed to learn the event rules. First the trajectories acquired by a tracking system ar...
Zhang Zhang, Kaiqi Huang, Tieniu Tan, Liangsheng W...
ROBOCUP
2001
Springer
111views Robotics» more  ROBOCUP 2001»
14 years 10 days ago
Evolving Fuzzy Logic Controllers for Sony Legged Robots
This paper presents an evolutionary approach to learning a fuzzy logic controller(FLC) employed for reactive behaviour control of Sony legged robots. The learning scheme is divided...
Dongbing Gu, Huosheng Hu