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» Collaborative Hierarchical Sparse Modeling
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SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 10 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
ER
2008
Springer
108views Database» more  ER 2008»
13 years 11 months ago
Automatic Extraction of Structurally Coherent Mini-Taxonomies
In this paper we demonstrate an automatic approach for emergent semantics modeling of ontologies. We follow the collaborative ontology construction method without the direct intera...
Khalid Saleem, Zohra Bellahsene
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 9 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
MOBIHOC
2006
ACM
14 years 8 months ago
Message ferry route design for sparse ad hoc networks with mobile nodes
Message ferrying is a networking paradigm where a special node, called a message ferry, facilitates the connectivity in a mobile ad hoc network where the nodes are sparsely deploy...
Muhammad Mukarram Bin Tariq, Mostafa H. Ammar, Ell...
TSP
2010
13 years 3 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...