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» Spectral clustering and transductive learning with multiple ...
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IJCAI
2001
13 years 9 months ago
Probabilistic Classification and Clustering in Relational Data
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Benjamin Taskar, Eran Segal, Daphne Koller
BIBM
2008
IEEE
142views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Using Global Sequence Similarity to Enhance Biological Sequence Labeling
Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...
Cornelia Caragea, Jivko Sinapov, Drena Dobbs, Vasa...
AAAI
2008
13 years 10 months ago
Multi-View Local Learning
The idea of local learning, i.e., classifying a particular example based on its neighbors, has been successfully applied to many semi-supervised and clustering problems recently. ...
Dan Zhang, Fei Wang, Changshui Zhang, Tao Li
ALT
2010
Springer
13 years 9 months ago
Towards General Algorithms for Grammatical Inference
Many algorithms for grammatical inference can be viewed as instances of a more general algorithm which maintains a set of primitive elements, which distributionally define sets of ...
Alexander Clark
ICML
2010
IEEE
13 years 5 months ago
Mining Clustering Dimensions
Many real-world datasets can be clustered along multiple dimensions. For example, text documents can be clustered not only by topic, but also by the author's gender or sentim...
Sajib Dasgupta, Vincent Ng