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» On the Vulnerability of Large Graphs
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AMW
2010
15 years 7 months ago
Run-time Optimization for Pipelined Systems
Traditional optimizers fail to pick good execution plans, when faced with increasingly complex queries and large data sets. This failure is even more acute in the context of XQuery...
Riham Abdel Kader, Maurice van Keulen, Peter A. Bo...
ICCV
2011
IEEE
14 years 6 months ago
Incremental On-line Semi-supervised Learning for Segmenting the Left Ventricle of the Heart from Ultrasound Data
Recently, there has been an increasing interest in the investigation of statistical pattern recognition models for the fully automatic segmentation of the left ventricle (LV) of t...
Gustavo Carneiro, Jacinto C. Nascimento
KDD
2002
ACM
182views Data Mining» more  KDD 2002»
16 years 6 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...
KDD
2010
ACM
197views Data Mining» more  KDD 2010»
15 years 4 months ago
Semi-supervised feature selection for graph classification
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Xiangnan Kong, Philip S. Yu
CAV
2006
Springer
121views Hardware» more  CAV 2006»
15 years 10 months ago
Deriving Small Unsatisfiable Cores with Dominators
Abstract. The problem of finding a small unsatisfiable core of an unsatisfiable CNF formula is addressed. The proposed algorithm, Trimmer, iterates over each internal node d in the...
Roman Gershman, Maya Koifman, Ofer Strichman