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» Sampling Methods for Unsupervised Learning
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INFOCOM
2006
IEEE
15 years 8 months ago
Sampling Techniques for Large, Dynamic Graphs
— Peer-to-peer systems are becoming increasingly popular, with millions of simultaneous users and a wide range of applications. Understanding existing systems and devising new pe...
Daniel Stutzbach, Reza Rejaie, Nick G. Duffield, S...
139
Voted
CATE
2004
190views Education» more  CATE 2004»
15 years 4 months ago
Enhancing Online Learning Performance: An Application of Data Mining Methods
Recently web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
138
Voted
AAAI
2010
15 years 4 months ago
Efficient Spectral Feature Selection with Minimum Redundancy
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Zheng Zhao, Lei Wang, Huan Liu
161
Voted
CSB
2004
IEEE
135views Bioinformatics» more  CSB 2004»
15 years 6 months ago
Selection of Patient Samples and Genes for Outcome Prediction
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Huiqing Liu, Jinyan Li, Limsoon Wong
129
Voted
ICML
2004
IEEE
15 years 8 months ago
Active learning using pre-clustering
The paper is concerned with two-class active learning. While the common approach for collecting data in active learning is to select samples close to the classification boundary,...
Hieu Tat Nguyen, Arnold W. M. Smeulders