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TCS
2010
13 years 7 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
TEC
2010
191views more  TEC 2010»
13 years 3 months ago
Particle Swarm Optimization Aided Orthogonal Forward Regression for Unified Data Modeling
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
Sheng Chen, Xia Hong, Chris J. Harris
ICASSP
2008
IEEE
14 years 3 months ago
Efficient calculation of adaptive interpolation filter with distortion modelling
A novel method is proposed to calculate the coefficients of adaptive interpolation filter used in hybrid video coders for improving the coding efficiency. The proposed algorithm f...
Kemal Ugur, Dmytro Rusanovskyy, Moncef Gabbouj
UIST
2005
ACM
14 years 2 months ago
Supporting interaction in augmented reality in the presence of uncertain spatial knowledge
A significant problem encounteredwhen building Augmented Reality (AR) systems is that all spatial knowledge about the world has uncertainty associated with it. This uncertainty m...
Enylton Machado Coelho, Blair MacIntyre, Simon Jul...
PAMI
2006
143views more  PAMI 2006»
13 years 9 months ago
Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
Shihao Ji, Balaji Krishnapuram, Lawrence Carin