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» Bayesian Approaches to Gaussian Mixture Modeling
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Book
778views
15 years 7 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
ICASSP
2009
IEEE
14 years 3 months ago
A semi-supervised learning approach to online audio background detection
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
Selina Chu, Shrikanth S. Narayanan, C.-C. Jay Kuo
IJCV
2002
172views more  IJCV 2002»
13 years 8 months ago
Using Multiple-Hypothesis Disparity Maps and Image Velocity for 3-D Motion Estimation
In this paper we explore a multiple hypothesis approach to estimating rigid motion from a moving stereo rig. More precisely, we introduce the use of Gaussian mixtures to model cor...
David Demirdjian, Trevor Darrell
ECAI
2010
Springer
13 years 10 months ago
Bayesian Monte Carlo for the Global Optimization of Expensive Functions
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
Perry Groot, Adriana Birlutiu, Tom Heskes
TVCG
2012
191views Hardware» more  TVCG 2012»
11 years 11 months ago
Live Speech Driven Head-and-Eye Motion Generators
—This paper describes a fully automated framework to generate realistic head motion, eye gaze, and eyelid motion simultaneously based on live (or recorded) speech input. Its cent...
Binh Huy Le, Xiaohan Ma, Zhigang Deng