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IJCNN
2000
IEEE
14 years 5 days 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
NN
2007
Springer
173views Neural Networks» more  NN 2007»
13 years 8 months ago
An enhanced self-organizing incremental neural network for online unsupervised learning
An enhanced self-organizing incremental neural network (ESOINN) is proposed to accomplish online unsupervised learning tasks. It improves the self-organizing incremental neural ne...
Shen Furao, Tomotaka Ogura, Osamu Hasegawa
COLING
2002
13 years 8 months ago
Unsupervised Named Entity Classification Models and their Ensembles
This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...
Jae-Ho Kim, In-Ho Kang, Key-Sun Choi
ICRA
2005
IEEE
176views Robotics» more  ICRA 2005»
14 years 2 months ago
Auto-supervised learning in the Bayesian Programming Framework
Domestic and real world robotics requires continuous learning of new skills and behaviors to interact with humans. Auto-supervised learning, a compromise between supervised and co...
Pierre Dangauthier, Pierre Bessière, Anne S...
ICML
2009
IEEE
14 years 9 months ago
Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
Linli Xu, Martha White, Dale Schuurmans