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» On the Vulnerability of Large Graphs
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ICML
2004
IEEE
16 years 7 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
KDD
2008
ACM
193views Data Mining» more  KDD 2008»
16 years 7 months ago
A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances
This work introduces a new family of link-based dissimilarity measures between nodes of a weighted directed graph. This measure, called the randomized shortest-path (RSP) dissimil...
Luh Yen, Marco Saerens, Amin Mantrach, Masashi Shi...
SDM
2009
SIAM
149views Data Mining» more  SDM 2009»
16 years 3 months ago
Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Graph classification is an increasingly important step in numerous application domains, such as function prediction of molecules and proteins, computerised scene analysis, and an...
Alexander J. Smola, Arthur Gretton, Hans-Peter Kri...
DM
2000
150views more  DM 2000»
15 years 6 months ago
A note on generalized chromatic number and generalized girth
Erdos proved that there are graphs with arbitrarily large girth and chromatic number. We study the extension of this for generalized chromatic numbers. Generalized graph coloring d...
Béla Bollobás, Douglas B. West
IANDC
2008
141views more  IANDC 2008»
15 years 6 months ago
Graph connectivity, partial words, and a theorem of Fine and Wilf
The problem of computing periods in words, or finite sequences of symbols from a finite alphabet, has important applications in several areas including data compression, string se...
Francine Blanchet-Sadri, Deepak Bal, Gautam Sisodi...