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» MuFeSaC: Learning When to Use Which Feature Detector
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KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 8 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
CSREAEEE
2008
199views Business» more  CSREAEEE 2008»
13 years 9 months ago
Progranimate - A Web Enabled Algorithmic Problem Solving Application
- This paper proposes the use of an interactive web based problem solving application that utilises flowchart based programming and code generation to address the issues faced by n...
Andrew Scott, Mike Watkins, Duncan McPhee
SAC
2006
ACM
13 years 7 months ago
Combining supervised and unsupervised monitoring for fault detection in distributed computing systems
Fast and accurate fault detection is becoming an essential component of management software for mission critical systems. A good fault detector makes possible to initiate repair a...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
ECML
2004
Springer
14 years 1 months ago
Using String Kernels to Identify Famous Performers from Their Playing Style
Abstract. In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characterstics of perf...
Craig Saunders, David R. Hardoon, John Shawe-Taylo...
ICPR
2006
IEEE
14 years 9 months ago
Isomap Based on the Image Euclidean Distance
Scientists find that the human perception is based on the similarity on the manifold of data set. Isometric feature mapping (Isomap) is one of the representative techniques of man...
Jie Chen, Ruiping Wang, Shiguang Shan, Wen Gao, Xi...