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KDD
2009
ACM
611views Data Mining» more  KDD 2009»
16 years 7 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 7 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
PODS
2009
ACM
86views Database» more  PODS 2009»
16 years 7 months ago
Reverse data exchange: coping with nulls
An inverse of a schema mapping M is intended to "undo" what M does, thus providing a way to perform "reverse" data exchange. In recent years, three different f...
Ronald Fagin, Phokion G. Kolaitis, Lucian Popa, Wa...
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
16 years 7 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 7 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
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