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PAKDD
2005
ACM
168views Data Mining» more  PAKDD 2005»
15 years 3 months ago
Adaptive Nonlinear Auto-Associative Modeling Through Manifold Learning
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
Junping Zhang, Stan Z. Li
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
15 years 3 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
IDEAL
2004
Springer
15 years 3 months ago
In-Situ Learning in Multi-net Systems
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...
Matthew C. Casey, Khurshid Ahmad
ROCAI
2004
Springer
15 years 3 months ago
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
Mathieu Roche, Jérôme Azé, Yve...
NIPS
2007
14 years 11 months ago
A Spectral Regularization Framework for Multi-Task Structure Learning
Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
Andreas Argyriou, Charles A. Micchelli, Massimilia...