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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
16 years 3 months ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy
COMGEO
2004
ACM
15 years 6 months ago
A local search approximation algorithm for k-means clustering
In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
ICSE
2008
IEEE-ACM
16 years 7 months ago
Precise memory leak detection for java software using container profiling
A memory leak in a Java program occurs when object references that are no longer needed are unnecessarily maintained. Such leaks are difficult to understand because static analyse...
Guoqing Xu, Atanas Rountev
ACSC
2005
IEEE
15 years 12 months ago
Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Kingsly Leung, Christopher Leckie
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
15 years 10 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar