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IJAR
2008
119views more  IJAR 2008»
13 years 8 months ago
Least committed basic belief density induced by a multivariate Gaussian: Formulation with applications
We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed b...
Francois Caron, Branko Ristic, Emmanuel Duflos, Ph...
TIT
1998
86views more  TIT 1998»
13 years 9 months ago
Maximin Performance of Binary-Input Channels with Uncertain Noise Distributions
—We consider uncertainty classes of noise distributions defined by a bound on the divergence with respect to a nominal noise distribution. The noise that maximizes the minimum e...
Andrew L. McKellips, Sergio Verdú
IROS
2007
IEEE
168views Robotics» more  IROS 2007»
14 years 4 months ago
Improving humanoid locomotive performance with learnt approximated dynamics via Gaussian processes for regression
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
TSP
2010
13 years 4 months ago
Complex Gaussian scale mixtures of complex wavelet coefficients
In this paper, we propose the complex Gaussian scale mixture (CGSM) to model the complex wavelet coefficients as an extension of the Gaussian scale mixture (GSM), which is for real...
Yothin Rakvongthai, An P. N. Vo, Soontorn Oraintar...
ICASSP
2009
IEEE
14 years 4 months ago
Time-space-sequential algorithms for distributed Bayesian state estimation in serial sensor networks
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
Ondrej Hlinka, Franz Hlawatsch