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SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
14 years 5 months ago
Hierarchical Linear Discriminant Analysis for Beamforming.
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Barry L. Drake, Haesun Park, Jaegul Choo
ECIR
2010
Springer
13 years 9 months ago
Text Clustering for Peer-to-Peer Networks with Probabilistic Guarantees
Text clustering is an established technique for improving quality in information retrieval, for both centralized and distributed environments. However, for highly distributed envir...
Odysseas Papapetrou, Wolf Siberski, Norbert Fuhr
ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
14 years 1 months ago
Ontologies Improve Text Document Clustering
Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large sets of documents into a small number of meaningful ...
Andreas Hotho, Steffen Staab, Gerd Stumme
ICANN
2005
Springer
14 years 1 months ago
High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...
Marc Strickert, Stefan Teichmann, Nese Sreenivasul...
SDM
2012
SIAM
261views Data Mining» more  SDM 2012»
11 years 10 months ago
Combining Active Learning and Dynamic Dimensionality Reduction
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
Mustafa Bilgic