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» New Algorithms for Enumerating All Maximal Cliques
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FIMI
2004
161views Data Mining» more  FIMI 2004»
14 years 11 months ago
ABS: Adaptive Borders Search of frequent itemsets
In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
Frédéric Flouvat, Fabien De Marchi, ...
JPDC
2007
86views more  JPDC 2007»
14 years 9 months ago
Performance evaluation of a new scheduling algorithm for distributed systems with security heterogeneity
High quality of security is increasingly critical for applications running on heterogeneous distributed systems. However, existing scheduling algorithms for heterogeneous distribu...
Tao Xie 0004, Xiao Qin
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 1 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
SIGIR
2002
ACM
14 years 9 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby
CVPR
2003
IEEE
15 years 11 months ago
Classification Based on Symmetric Maximized Minimal Distance in Subspace (SMMS)
We introduce a new classification algorithm based on the concept of Symmetric Maximized Minimal distance in Subspace (SMMS). Given the training data of authentic samples and impos...
Wende Zhang, Tsuhan Chen