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ICIP
2007
IEEE
16 years 2 months ago
Monocular Tracking 3D People By Gaussian Process Spatio-Temporal Variable Model
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
Junbiao Pang, Laiyun Qing, Qingming Huang, Shuqian...
TIT
2008
84views more  TIT 2008»
14 years 11 months ago
A Note on Rate-Distortion Functions for Nonstationary Gaussian Autoregressive Processes
Source coding theorems and Shannon rate-distortion functions were studied for the discrete-time Wiener process by Berger and generalized to nonstationary Gaussian autoregressive p...
Robert M. Gray, Takeshi Hashimoto
106
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Data-driven fMRI group classification using connected components and Gaussian process classifiers
Functional magnetic resonance imaging (fMRI) is a popular tool for studying brain activity due to its non-invasiveness. Conventionally an expected response needs to be available f...
Sarah Lee, Fernando Zelaya, Yohan Samarasinghe, St...
CIKM
2008
Springer
15 years 2 months ago
A sparse gaussian processes classification framework for fast tag suggestions
Tagged data is rapidly becoming more available on the World Wide Web. Web sites which populate tagging services offer a good way for Internet users to share their knowledge. An in...
Yang Song, Lu Zhang 0007, C. Lee Giles
118
Voted
UAI
2008
15 years 2 months ago
Modelling local and global phenomena with sparse Gaussian processes
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
Jarno Vanhatalo, Aki Vehtari