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» A Markov Chain Monte Carlo Approach to Stereovision
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IJCNN
2000
IEEE
15 years 1 months ago
On MCMC Sampling in Bayesian MLP Neural Networks
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Aki Vehtari, Simo Särkkä, Jouko Lampinen
AAAI
2006
14 years 11 months ago
Probabilistic Self-Localization for Sensor Networks
This paper describes a technique for the probabilistic self-localization of a sensor network based on noisy inter-sensor range data. Our method is based on a number of parallel in...
Dimitri Marinakis, Gregory Dudek
ACCV
2006
Springer
15 years 3 months ago
Tracking Targets Via Particle Based Belief Propagation
We first formulate multiple targets tracking problem in a dynamic Markov network(DMN)which is derived from a MRFs for joint target state and a binary process for occlusion of dual...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
CVPR
2012
IEEE
12 years 11 months ago
A Unified Framework for Event Summarization and Rare Event Detection
A novel approach for event summarization and rare event detection is proposed. Unlike conventional methods that deal with event summarization and rare event detection independently...
Junseok Kwon and Kyoung Mu Lee
80
Voted
STOC
1997
ACM
125views Algorithms» more  STOC 1997»
15 years 1 months ago
An Interruptible Algorithm for Perfect Sampling via Markov Chains
For a large class of examples arising in statistical physics known as attractive spin systems (e.g., the Ising model), one seeks to sample from a probability distribution π on an...
James Allen Fill