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GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 8 months 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
GCB
2000
Springer
99views Biometrics» more  GCB 2000»
15 years 7 months ago
Structure Motif Discovery and Mining the PDB
We describe an algorithm for the automatic discovery of recurring patterns in protein structures. The patterns consist of individual residues having a defined order along the prote...
Inge Jonassen, Ingvar Eidhammer, Darrell Conklin, ...
ECCV
2010
Springer
15 years 6 months ago
Object Segmentation by Long Term Analysis of Point Trajectories
Unsupervised learning requires a grouping step that defines which data belong together. A natural way of grouping in images is the segmentation of objects or parts of objects. Whi...
EMNLP
2007
15 years 5 months ago
Building Lexicon for Sentiment Analysis from Massive Collection of HTML Documents
Recognizing polarity requires a list of polar words and phrases. For the purpose of building such lexicon automatically, a lot of studies have investigated (semi-) unsupervised me...
Nobuhiro Kaji, Masaru Kitsuregawa
MVA
2007
154views Computer Vision» more  MVA 2007»
15 years 5 months ago
Fisher Non-negative Matrix Factorization with Pairwise Weighting
Non-negative matrix factorization (NMF) is a powerful feature extraction method for finding parts-based, linear representations of non-negative data . Inherently, it is unsupervis...
Xi Li, Kazuhiro Fukui