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» Online Rule Learning via Weighted Model Counting
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ECAI
2008
Springer
13 years 6 months ago
Online Rule Learning via Weighted Model Counting
Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
Frédéric Koriche
ICIC
2007
Springer
13 years 11 months ago
Fuzzy Modeling Via On-Line Clustering and Support Vector Machine
Abstract. This paper describes a novel fuzzy rule-based modeling approach for some slow industrial processses. Structure identification is realized by clustering and support vecto...
Julio César Tovar, Wen Yu, Xiaoou Li
NIPS
1998
13 years 6 months ago
Global Optimisation of Neural Network Models via Sequential Sampling
We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
João F. G. de Freitas, Mahesan Niranjan, Ar...
ICCV
2009
IEEE
13 years 2 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu
IRI
2007
IEEE
13 years 11 months ago
Automated Multimedia Systems Training Using Association Rule Mining
User feedback is widely deployed in recent multimedia research to refine retrieval performance. However, most of the existing online learning algorithms handle interactions of a s...
Na Zhao, Shu-Ching Chen, Stuart Harvey Rubin