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» A General Framework for Graph Sparsification
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145
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SODA
2007
ACM
76views Algorithms» more  SODA 2007»
15 years 5 months ago
An unbiased pointing operator for unlabeled structures, with applications to counting and sampling
We introduce a general method to count and randomly sample unlabeled combinatorial structures. The approach is based on pointing unlabeled structures in an “unbiased” way, i.e...
Manuel Bodirsky, Éric Fusy, Mihyun Kang, St...
139
Voted
PAMI
2006
117views more  PAMI 2006»
15 years 3 months ago
Metric Learning for Text Documents
High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from ...
Guy Lebanon
137
Voted
SIGMOD
2010
ACM
196views Database» more  SIGMOD 2010»
15 years 7 months ago
Connected substructure similarity search
Substructure similarity search is to retrieve graphs that approximately contain a given query graph. It has many applications, e.g., detecting similar functions among chemical com...
Haichuan Shang, Xuemin Lin, Ying Zhang, Jeffrey Xu...
171
Voted
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 6 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
147
Voted
PLDI
2012
ACM
13 years 6 months ago
Parallelizing top-down interprocedural analyses
Modularity is a central theme in any scalable program analysis. The core idea in a modular analysis is to build summaries at procedure boundaries, and use the summary of a procedu...
Aws Albarghouthi, Rahul Kumar, Aditya V. Nori, Sri...