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» Evaluating learning algorithms and classifiers
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BMCBI
2007
178views more  BMCBI 2007»
13 years 10 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
WWW
2009
ACM
14 years 11 months ago
Automated synthesis of composite services with correctness guarantee
In this paper, we propose a novel approach for composing existing web services to satisfy the correctness constraints to the design, including freeness of deadlock and unspecified...
Ting Deng, Jinpeng Huai, Xianxian Li, Zongxia Du, ...
RECSYS
2009
ACM
14 years 4 months ago
Learning to recommend helpful hotel reviews
User-generated reviews are a common and valuable source of product information, yet little attention has been paid as to how best to present them to end-users. In this paper, we d...
Michael P. O'Mahony, Barry Smyth
ICASSP
2008
IEEE
14 years 4 months ago
Discriminative learning for optimizing detection performance in spoken language recognition
We propose novel approaches for optimizing the detection performance in spoken language recognition. Two objective functions are designed to directly relate model parameters to tw...
Donglai Zhu, Haizhou Li, Bin Ma, Chin-Hui Lee
PKDD
2000
Springer
100views Data Mining» more  PKDD 2000»
14 years 1 months ago
Learning Right Sized Belief Networks by Means of a Hybrid Methodology
Previous algoritms for the construction of belief networks structures from data are mainly based either on independence criteria or on scoring metrics. The aim of this paper is to ...
Silvia Acid, Luis M. de Campos