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80
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ICIP
2005
IEEE
16 years 2 months ago
Sampling in practice: is the best reconstruction space bandlimited?
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant " space, ...
Sathish Ramani, Dimitri Van De Ville, Michael Unse...
190
Voted
CVPR
2010
IEEE
13 years 9 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
JMLR
2010
137views more  JMLR 2010»
14 years 7 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
109
Voted
ICML
2007
IEEE
16 years 1 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
129
Voted
IEEECIT
2010
IEEE
14 years 11 months ago
Metadata-Based Adaptive Sampling for Energy-Efficient Collaborative Target Tracking in Wireless Sensor Networks
—The increasingly complex roles for which Wireless Sensor Networks (WSNs) are being employed have driven the desire for energy-efficient reliable target tracking. In this paper, ...
Yousef E. M. Hamouda, Chris Phillips