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PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 1 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
JUCS
2007
118views more  JUCS 2007»
14 years 9 months ago
Satisfying Assignments of Random Boolean Constraint Satisfaction Problems: Clusters and Overlaps
: The distribution of overlaps of solutions of a random constraint satisfaction problem (CSP) is an indicator of the overall geometry of its solution space. For random k-SAT, nonri...
Gabriel Istrate
ICALP
2009
Springer
15 years 10 months ago
Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems
Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
Nir Ailon, Edo Liberty
ICCAD
2005
IEEE
98views Hardware» more  ICCAD 2005»
15 years 6 months ago
Clustering for processing rate optimization
Clustering (or partitioning) is a crucial step between logic synthesis and physical design in the layout of a large scale design. A design verified at the logic synthesis level m...
Chuan Lin, Jia Wang, Hai Zhou
ICPADS
2006
IEEE
15 years 3 months ago
Memory and Network Bandwidth Aware Scheduling of Multiprogrammed Workloads on Clusters of SMPs
Symmetric Multiprocessors (SMPs), combined with modern interconnection technologies are commonly used to build cost-effective compute clusters. However, contention among processor...
Evangelos Koukis, Nectarios Koziris