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ICONIP
2009
13 years 6 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
SIAMCO
2000
117views more  SIAMCO 2000»
13 years 8 months ago
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
Vivek S. Borkar, Sean P. Meyn
ICA
2007
Springer
14 years 28 days ago
Phase-Aware Non-negative Spectrogram Factorization
Non-negative spectrogram factorization has been proposed for single-channel source separation tasks. These methods operate on the magnitude or power spectrogram of the input mixtur...
R. Mitchell Parry, Irfan A. Essa
COLING
2008
13 years 10 months ago
Metric Learning for Synonym Acquisition
The distance or similarity metric plays an important role in many natural language processing (NLP) tasks. Previous studies have demonstrated the effectiveness of a number of metr...
Nobuyuki Shimizu, Masato Hagiwara, Yasuhiro Ogawa,...
ICCBR
2007
Springer
14 years 3 months ago
Case-Based Reasoning for Invoice Analysis and Recognition
This paper introduces the approach CBRDIA (Case Based Reasoning for Document Invoice Analysis) which uses the principles of case-based reasoning to analyze, recognize and interpret...
Hatem Hamza, Yolande Belaïd, Abdel Belaï...