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» Unsupervised feature selection using a neuro-fuzzy approach
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ICPR
2010
IEEE
15 years 6 months ago
Bayesian Inference for Nonnegative Matrix Factor Deconvolution Models
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...
Serap Kirbiz, Ali Taylan Cemgil, Bilge Gunsel
IJCNN
2007
IEEE
15 years 6 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
SPEECH
2010
154views more  SPEECH 2010»
14 years 6 months ago
Long story short - Global unsupervised models for keyphrase based meeting summarization
act 11 We analyze and compare two different methods for unsupervised extractive spontaneous speech summarization in the meeting 12 domain. Based on utterance comparison, we introdu...
Korbinian Riedhammer, Benoît Favre, Dilek Ha...
IJCNN
2000
IEEE
15 years 3 months ago
Competing Hidden Markov Models on the Self-Organizing Map
This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
Panu Somervuo
ICIP
2009
IEEE
14 years 9 months ago
A hierarchical graph-based markovian clustering approach for the unsupervised segmentation of textured color images
In this paper, a new unsupervised hierarchical approach to textured color images segmentation is proposed. To this end, we have designed a two-step procedure based on a grey-scale...
Rachid Hedjam, Max Mignotte