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PAKDD
2004
ACM
96views Data Mining» more  PAKDD 2004»
14 years 24 days ago
Spectral Energy Minimization for Semi-supervised Learning
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
Chun Hung Li, Zhi-Li Wu
IJCAI
1989
13 years 8 months ago
Training Feedforward Neural Networks Using Genetic Algorithms
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
David J. Montana, Lawrence Davis
MLMI
2005
Springer
14 years 28 days ago
Improving the Performance of Acoustic Event Classification by Selecting and Combining Information Sources Using the Fuzzy Integr
Acoustic events produced in meeting-room-like environments may carry information useful for perceptually aware interfaces. In this paper, we focus on the problem of combining diffe...
Andrey Temko, Dusan Macho, Climent Nadeu
ICIP
2009
IEEE
14 years 8 months ago
Parking Space Detection From Video By Augmenting Training Dataset
Auto parking techniques are attracting more attention these days. In this paper, we develop an image-based method to estimate the depth contour in parking areas. Our algorithm is ...
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
13 years 11 months ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles