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ICDM
2008
IEEE
97views Data Mining» more  ICDM 2008»
16 years 1 months ago
Semi-supervised Learning from General Unlabeled Data
We consider the problem of Semi-supervised Learning (SSL) from general unlabeled data, which may contain irrelevant samples. Within the binary setting, our model manages to better...
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. L...
MSR
2005
ACM
16 years 25 days ago
Collaboration using OSSmole: a repository of FLOSS data and analyses
This paper introduces a collaborative project OSSmole which collects, shares, and stores comparable data and analyses of free, libre and open source software (FLOSS) development f...
Megan Conklin, James Howison, Kevin Crowston
DKE
2008
109views more  DKE 2008»
15 years 7 months ago
Deterministic algorithms for sampling count data
Processing and extracting meaningful knowledge from count data is an important problem in data mining. The volume of data is increasing dramatically as the data is generated by da...
Hüseyin Akcan, Alex Astashyn, Hervé Br...
PKDD
2010
Springer
183views Data Mining» more  PKDD 2010»
15 years 5 months ago
Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space
Data stream classification poses many challenges, most of which are not addressed by the state-of-the-art. We present DXMiner, which addresses four major challenges to data stream ...
Mohammad M. Masud, Qing Chen, Jing Gao, Latifur Kh...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
15 years 8 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar