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» Similarity measures for multidimensional data
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 4 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
ICDM
2010
IEEE
276views Data Mining» more  ICDM 2010»
15 years 2 months ago
Accelerating Dynamic Time Warping Subsequence Search with GPUs and FPGAs
Many time series data mining problems require subsequence similarity search as a subroutine. While this can be performed with any distance measure, and dozens of distance measures ...
Doruk Sart, Abdullah Mueen, Walid A. Najjar, Eamon...
BMCBI
2007
126views more  BMCBI 2007»
15 years 4 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
ICDM
2005
IEEE
185views Data Mining» more  ICDM 2005»
15 years 9 months ago
Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping
The problem of record linkage focuses on determining whether two object descriptions refer to the same underlying entity. Addressing this problem effectively has many practical ap...
Mikhail Bilenko, Sugato Basu, Mehran Sahami
FGR
2008
IEEE
132views Biometrics» more  FGR 2008»
15 years 10 months ago
Logit-RankBoost with pruning for face recognition
In this paper a novel ranking-based face recognition (FR) scheme is proposed. Compared with classical twoclass (intra/extra person) and multi-class (each person a single class) sc...
Bangpeng Yao, Haizhou Ai, Shihong Lao