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» Learning to learn with the informative vector machine
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 7 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
180
Voted
IEEECIT
2007
IEEE
16 years 1 months ago
An Experimental Study on Feature Subset Selection Methods
In the field of machine learning and pattern recognition, feature subset selection is an important area, where many approaches have been proposed. In this paper, we choose some fe...
Chulmin Yun, Donghyuk Shin, Hyunsung Jo, Jihoon Ya...
CIKM
1999
Springer
15 years 11 months ago
Training a Selection Function for Extraction
In this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence ...
Chin-Yew Lin
SIGKDD
2010
154views more  SIGKDD 2010»
15 years 1 months ago
A brief survey on sequence classification
Sequence classification has a broad range of applications such as genomic analysis, information retrieval, health informatics, finance, and abnormal detection. Different from the ...
Zhengzheng Xing, Jian Pei, Eamonn J. Keogh
ICASSP
2011
IEEE
14 years 10 months ago
Trading off communications bandwidth with accuracy in adaptive diffusion networks
In this paper, a novel algorithm for bandwidth reduction in adaptive distributed learning is introduced. We deal with diffusion networks, in which the nodes cooperate with each ot...
Symeon Chouvardas, Konstantinos Slavakis, Sergios ...