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IOR
2006
163views more  IOR 2006»
13 years 7 months ago
Adaptive Importance Sampling Technique for Markov Chains Using Stochastic Approximation
For a discrete-time finite-state Markov chain, we develop an adaptive importance sampling scheme to estimate the expected total cost before hitting a set of terminal states. This s...
T. P. I. Ahamed, Vivek S. Borkar, S. Juneja
ICIAP
2007
ACM
14 years 7 months ago
An information theoretic rule for sample size adaptation in particle filtering
To become robust, a tracking algorithm must be able to support uncertainty and ambiguity often inherently present in the data in form of occlusion and clutter. This comes usually ...
Oswald Lanz
CSE
2009
IEEE
14 years 2 months ago
Self-Tuning the Parameter of Adaptive Non-linear Sampling Method for Flow Statistics
—Flow statistics is a basic task of passive measurement and has been widely used to characterize the state of the network. Adaptive Non-Linear Sampling (ANLS)is one of the most a...
Chengchen Hu, Bin Liu
TSP
2010
13 years 2 months ago
Adaptive sampling rate correction for acoustic echo control in voice-over-IP
Abstract--Hands-free terminals for speech communication employ adaptive filters to reduce echoes resulting from the acoustic coupling between loudspeaker and microphone. When using...
Matthias Pawig, Gerald Enzner, Peter Vary
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 9 months ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard