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IVC
2010
128views more  IVC 2010»
13 years 7 months ago
Online kernel density estimation for interactive learning
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...
Matej Kristan, Danijel Skocaj, Ales Leonardis
ICPR
2004
IEEE
14 years 9 months ago
Learning Spatial Context from Tracking using Penalised Likelihoods
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
Hammadi Nait-Charif, Stephen J. McKenna
ICASSP
2010
IEEE
13 years 9 months ago
Statistical approach to enhancing esophageal speech based on Gaussian mixture models
This paper presents a novel method of enhancing esophageal speech using statistical voice conversion. Esophageal speech is one of the alternative speaking methods for laryngectome...
Hironori Doi, Keigo Nakamura, Tomoki Toda, Hiroshi...
PAMI
2008
161views more  PAMI 2008»
13 years 8 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
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