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PR
2006
141views more  PR 2006»
13 years 8 months ago
Relaxational metric adaptation and its application to semi-supervised clustering and content-based image retrieval
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
Hong Chang, Dit-Yan Yeung, William K. Cheung
RECOMB
2010
Springer
13 years 10 months ago
Leveraging Sequence Classification by Taxonomy-Based Multitask Learning
In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 8 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
WWW
2005
ACM
14 years 9 months ago
Ranking definitions with supervised learning methods
This paper is concerned with the problem of definition search. Specifically, given a term, we are to retrieve definitional excerpts of the term and rank the extracted excerpts acc...
Jun Xu, Yunbo Cao, Hang Li, Min Zhao
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
14 years 2 days ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles