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KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 9 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
113
Voted
CVPR
2010
IEEE
15 years 12 months ago
Hierarchical Convolutional Sparse Image Decomposition
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew Zeiler, Dilip Krishnan, Graham Taylor, Rob...
IDA
2009
Springer
15 years 10 months ago
How to Control Clustering Results? Flexible Clustering Aggregation
One of the most important and challenging questions in the area of clustering is how to choose the best-fitting algorithm and parameterization to obtain an optiml clustering for t...
Martin Hahmann, Peter Benjamin Volk, Frank Rosenth...
BIBM
2008
IEEE
101views Bioinformatics» more  BIBM 2008»
15 years 10 months ago
Comparing and Clustering Flow Cytometry Data
Flow cytometry technique produces large, multidimensional datasets of properties of individual cells that are helpful for biomedical science and clinical research. This paper expl...
Lin Liu, Li Xiong, James J. Lu, Kim M. Gernert, Vi...
126
Voted
GFKL
2007
Springer
123views Data Mining» more  GFKL 2007»
15 years 10 months ago
Projecting Dialect Distances to Geography: Bootstrap Clustering vs. Noisy Clustering
Abstract. Dialectometry produces aggregate distance matrices in which a distance is specified for each pair of sites. By projecting groups obtained by clustering onto geography on...
John Nerbonne, Peter Kleiweg, Wilbert Heeringa, Fr...