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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
TOIS
2010
128views more  TOIS 2010»
13 years 6 months ago
Learning author-topic models from text corpora
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
ECIS
2004
13 years 9 months ago
Value-based business modelling for network organizations: lessons learned from the electricity sector
Speed and availability of information, delivered in past years by Internet technologies, made it easier for any company to outsource primary activities, which resulted in unbundli...
Vera Kartseva, Jaap Gordijn, Yao-Hua Tan
ICGI
1998
Springer
14 years 8 hour ago
Learning Stochastic Finite Automata from Experts
We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
Colin de la Higuera
EMNLP
2008
13 years 9 months ago
Discriminative Learning of Selectional Preference from Unlabeled Text
We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
Shane Bergsma, Dekang Lin, Randy Goebel