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ECML
2006
Springer
15 years 8 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
ICASSP
2011
IEEE
14 years 8 months ago
Distributed routing in networks using affinity propagation
This paper applies affinity propagation (AP) to develop distributed solutions for routing over networks. AP is a message passing algorithm for unsupervised learning. This paper d...
Manohar Shamaiah, Sang Hyun Lee, Sriram Vishwanath...
ICML
2010
IEEE
15 years 5 months ago
Unsupervised Risk Stratification in Clinical Datasets: Identifying Patients at Risk of Rare Outcomes
Most existing algorithms for clinical risk stratification rely on labeled training data. Collecting this data is challenging for clinical conditions where only a small percentage ...
Zeeshan Syed, Ilan Rubinfeld
BMCBI
2010
155views more  BMCBI 2010»
15 years 4 months ago
A flexible R package for nonnegative matrix factorization
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Renaud Gaujoux, Cathal Seoighe
FLAIRS
2006
15 years 5 months ago
Corpus Based Unsupervised Labeling of Documents
Text categorization involves mapping of documents to a fixed set of labels. A similar but equally important problem is that of assigning labels to large corpora. With a deluge of ...
Delip Rao, Deepak P, Deepak Khemani