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ICIAP
2005
ACM
15 years 9 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
CIKM
2010
Springer
14 years 6 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
14 years 7 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
14 years 11 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
77
Voted
SAMT
2007
Springer
211views Multimedia» more  SAMT 2007»
15 years 3 months ago
An Architecture for Mining Resources Complementary to Audio-Visual Streams
Abstract. In this paper we attempt to characterize resources of information complementary to audio-visual (A/V) streams and propose their usage for enriching A/V data with semantic...
Jan Nemrava, Paul Buitelaar, Thierry Declerck, Voj...