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» Anti-Ramsey properties of random graphs
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ICML
2007
IEEE
14 years 9 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ICS
2010
Tsinghua U.
14 years 6 months ago
Local Algorithms for Finding Interesting Individuals in Large Networks
: We initiate the study of local, sublinear time algorithms for finding vertices with extreme topological properties -- such as high degree or clustering coefficient -- in large so...
Mickey Brautbar, Michael Kearns
CVPR
2012
IEEE
11 years 11 months ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 9 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
IMC
2010
ACM
13 years 6 months ago
Measuring the mixing time of social graphs
Social networks provide interesting algorithmic properties that can be used to bootstrap the security of distributed systems. For example, it is widely believed that social networ...
Abedelaziz Mohaisen, Aaram Yun, Yongdae Kim