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» Hierarchical Unsupervised Learning
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COLING
2008
15 years 5 months ago
Looking for Trouble
This paper presents a method for mining potential troubles or obstacles related to the use of a given object. Some example instances of this relation are medicine, side effect and...
Stijn De Saeger, Kentaro Torisawa, Jun'ichi Kazama
113
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ICMLA
2008
15 years 5 months ago
Semi-supervised IFA with Prior Knowledge on the Mixing Process: An Application to a Railway Device Diagnosis
Independent Factor Analysis (IFA) is a well known method used to recover independent components from their linear observed mixtures without any knowledge on the mixing process. Su...
Etienne Côme, Zohra Leila Cherfi, Latifa Ouk...
157
Voted
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
15 years 5 months ago
Semi-supervised Feature Selection via Spectral Analysis
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
Zheng Zhao, Huan Liu
150
Voted
NIPS
2000
15 years 5 months ago
Rate-coded Restricted Boltzmann Machines for Face Recognition
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Yee Whye Teh, Geoffrey E. Hinton
136
Voted
JNCA
2007
136views more  JNCA 2007»
15 years 3 months ago
Adaptive anomaly detection with evolving connectionist systems
Anomaly detection holds great potential for detecting previously unknown attacks. In order to be effective in a practical environment, anomaly detection systems have to be capable...
Yihua Liao, V. Rao Vemuri, Alejandro Pasos