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CIKM
2009
Springer
13 years 11 months ago
Improving binary classification on text problems using differential word features
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 8 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
KDD
2008
ACM
206views Data Mining» more  KDD 2008»
14 years 7 months ago
Identifying biologically relevant genes via multiple heterogeneous data sources
Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioin...
Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Y...
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
14 years 1 months ago
A destructive evolutionary process: a pilot implementation
This paper describes the application of evolutionary search to the problem of Flash memory wear-out. The operating parameters of Flash memory are notoriously difficult to determin...
Joe Sullivan, Conor Ryan
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
14 years 7 months ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen