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PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 7 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. ...
121
Voted
JUCS
2007
118views more  JUCS 2007»
15 years 3 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
16 years 3 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
103
Voted
ICCAD
2005
IEEE
98views Hardware» more  ICCAD 2005»
16 years 10 days 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 9 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