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» Testing homogeneity of a large data set by bootstrapping
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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 8 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
SIGMOD
2002
ACM
132views Database» more  SIGMOD 2002»
14 years 7 months ago
Clustering by pattern similarity in large data sets
Clustering is the process of grouping a set of objects into classes of similar objects. Although definitions of similarity vary from one clustering model to another, in most of th...
Haixun Wang, Wei Wang 0010, Jiong Yang, Philip S. ...
RECOMB
2008
Springer
14 years 7 months ago
Bootstrapping the Interactome: Unsupervised Identification of Protein Complexes in Yeast
Protein interactions and complexes are major components of biological systems. Recent genome-wide applications of tandem affinity purification (TAP) in yeast have increased signifi...
Caroline C. Friedel, Jan Krumsiek, Ralf Zimmer
ITC
2002
IEEE
72views Hardware» more  ITC 2002»
14 years 9 days ago
Test Point Insertion that Facilitates ATPG in Reducing Test Time and Data Volume
Efficient production testing is frequently hampered because current digital circuits require test sets which are too large. These test sets can be reduced significantly by means...
M. J. Geuzebroek, J. Th. van der Linden, A. J. van...
ICASSP
2011
IEEE
12 years 11 months ago
Statistical analysis of multi-channel detection using data from airborne AESA radar
We investigate the ground clutter homogeneity and target detection performance using airborne multi-channel AESA (Active Electronically Scanned Array) radar data from flight trial...
Johan Degerman, Thomas Pernstal, Magnus Gisselfalt...