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» On a theory of learning with similarity functions
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BIBE
2001
IEEE
13 years 11 months ago
Gene Classification using Expression Profiles: A Feasibility Study
As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus from structural genomics to functional genomi...
Michihiro Kuramochi, George Karypis
IJON
2007
88views more  IJON 2007»
13 years 7 months ago
Information maximization in face processing
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
Marian Stewart Bartlett
NIPS
1998
13 years 9 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
BMCBI
2005
117views more  BMCBI 2005»
13 years 7 months ago
An SVM-based system for predicting protein subnuclear localizations
Background: The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computatio...
Zhengdeng Lei, Yang Dai
CORR
2010
Springer
163views Education» more  CORR 2010»
13 years 6 months ago
Faster Rates for training Max-Margin Markov Networks
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan