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KDD
2005
ACM
157views Data Mining» more  KDD 2005»
16 years 7 months ago
A fast kernel-based multilevel algorithm for graph clustering
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
KDD
2002
ACM
182views Data Mining» more  KDD 2002»
16 years 7 months ago
ANF: a fast and scalable tool for data mining in massive graphs
Graphs are an increasingly important data source, with such important graphs as the Internet and the Web. Other familiar graphs include CAD circuits, phone records, gene sequences...
Christopher R. Palmer, Phillip B. Gibbons, Christo...
RECOMB
2006
Springer
16 years 7 months ago
RNA Secondary Structure Prediction Via Energy Density Minimization
Abstract. There is a resurgence of interest in RNA secondary structure prediction problem (a.k.a. the RNA folding problem) due to the discovery of many new families of non-coding R...
Can Alkan, Emre Karakoç, Süleyman Cenk...
STOC
2005
ACM
135views Algorithms» more  STOC 2005»
16 years 6 months ago
Quadratic forms on graphs
We introduce a new graph parameter, called the Grothendieck constant of a graph G = (V, E), which is defined as the least constant K such that for every A : E R, sup f:V S|V |-1 ...
Noga Alon, Konstantin Makarychev, Yury Makarychev,...
STOC
2004
ACM
150views Algorithms» more  STOC 2004»
16 years 6 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking