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» Boosting Spectral Partitioning by Sampling and Iteration
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ISAAC
2005
Springer
111views Algorithms» more  ISAAC 2005»
13 years 10 months ago
Boosting Spectral Partitioning by Sampling and Iteration
A partition of a set of n items is a grouping of the items into k disjoint classes of equal size. Any partition can be modeled as a graph: the items become the vertices of the grap...
Joachim Giesen, Dieter Mitsche
KDD
2007
ACM
181views Data Mining» more  KDD 2007»
14 years 5 months ago
BoostCluster: boosting clustering by pairwise constraints
Data clustering is an important task in many disciplines. A large number of studies have attempted to improve clustering by using the side information that is often encoded as pai...
Yi Liu, Rong Jin, Anil K. Jain
ICASSP
2011
IEEE
12 years 8 months ago
A single snapshot optimal filtering method for fundamental frequency estimation
Recently, optimal linearly constrained minimum variance (LCMV) filtering methods have been applied for fundamental frequency estimation. Like many other fundamental frequency est...
Jesper Rindom Jensen, Mads Groesboll Christensen, ...