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» Theory and Use of the EM Algorithm
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ICML
2009
IEEE
16 years 7 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
WWW
2009
ACM
16 years 7 months ago
Learning to tag
Social tagging provides valuable and crucial information for large-scale web image retrieval. It is ontology-free and easy to obtain; however, irrelevant tags frequently appear, a...
Lei Wu, Linjun Yang, Nenghai Yu, Xian-Sheng Hua
WWW
2004
ACM
16 years 7 months ago
The webgraph framework I: compression techniques
Studying Web graphs is often difficult due to their large size. Recently, several proposals have been published about various techniques that allow to store a Web graph in memory ...
Paolo Boldi, Sebastiano Vigna
STOC
2009
ACM
87views Algorithms» more  STOC 2009»
16 years 7 months ago
Randomly supported independence and resistance
We prove that for any positive integer k, there is a constant ck such that a randomly selected set of cknk log n Boolean vectors with high probability supports a balanced k-wise i...
Per Austrin, Johan Håstad
KDD
2006
ACM
136views Data Mining» more  KDD 2006»
16 years 6 months ago
Very sparse random projections
There has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. Let A Rn...
Ping Li, Trevor Hastie, Kenneth Ward Church