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SSPR
2004
Springer
15 years 10 months ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
16 years 2 months ago
Multiple Kernel Clustering.
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Bin Zhao, James T. Kwok, Changshui Zhang
SAC
2008
ACM
15 years 4 months ago
Efficient concept clustering for ontology learning using an event life cycle on the web
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
Sangsoo Sung, Seokkyung Chung, Dennis McLeod
ICMLA
2010
15 years 3 months ago
A New Approach to Classification with the Least Number of Features
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separati...
Sascha Klement, Thomas Martinetz
EUSFLAT
2009
132views Fuzzy Logic» more  EUSFLAT 2009»
15 years 2 months ago
Modeling Position Specificity in Sequence Kernels by Fuzzy Equivalence Relations
This paper demonstrates that several known sequence kernels can be expressed in a unified framework in which the position specificity is modeled by fuzzy equivalence relations. In ...
Ulrich Bodenhofer, Karin Schwarzbauer, Mihaela Ion...