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» Factorial Learning and the EM Algorithm
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ICML
2004
IEEE
14 years 8 months ago
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Zhihua Zhang, Dit-Yan Yeung, James T. Kwok
ICDM
2007
IEEE
187views Data Mining» more  ICDM 2007»
14 years 1 months ago
Statistical Learning Algorithm for Tree Similarity
Tree edit distance is one of the most frequently used distance measures for comparing trees. When using the tree edit distance, we need to determine the cost of each operation, bu...
Atsuhiro Takasu, Daiji Fukagawa, Tatsuya Akutsu
ML
2006
ACM
121views Machine Learning» more  ML 2006»
13 years 7 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
12 years 11 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
13 years 6 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas