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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 7 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
BMCBI
2006
118views more  BMCBI 2006»
15 years 6 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
BCSHCI
2009
15 years 4 months ago
Virtual world users evaluated according to environment design, task based and affective attention measures
This paper presents research that engages with virtual worlds for education users to understand design of these applications for their needs. An in-depth multi-method investigatio...
Breen Sweeney, Anne Adams
CIKM
2008
Springer
15 years 8 months ago
Trada: tree based ranking function adaptation
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...
COLT
2010
Springer
15 years 4 months ago
Toward Learning Gaussian Mixtures with Arbitrary Separation
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Mikhail Belkin, Kaushik Sinha