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» Approximate Inference and Constrained Optimization
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TCOM
2011
155views more  TCOM 2011»
13 years 2 months ago
Asymptotically Optimal Model Estimation for Quantization
—Using high-rate theory approximations we introduce flexible practical quantizers based on possibly non-Gaussian models in both the constrained resolution (CR) and the constrain...
Alexey Ozerov, W. Bastiaan Kleijn
ECCV
2008
Springer
14 years 9 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
IJRR
2008
151views more  IJRR 2008»
13 years 7 months ago
Trajectory Optimization using Reinforcement Learning for Map Exploration
Automatically building maps from sensor data is a necessary and fundamental skill for mobile robots; as a result, considerable research attention has focused on the technical chall...
Thomas Kollar, Nicholas Roy
INFOCOM
2008
IEEE
14 years 2 months ago
Minimum Cost Data Aggregation with Localized Processing for Statistical Inference
—The problem of minimum cost in-network fusion of measurements, collected from distributed sensors via multihop routing is considered. A designated fusion center performs an opti...
Animashree Anandkumar, Lang Tong, Ananthram Swami,...
ESSMAC
2003
Springer
14 years 24 days ago
Simultaneous Localization and Surveying with Multiple Agents
We apply a constrained Hidden Markov Model architecture to the problem of simultaneous localization and surveying from sensor logs of mobile agents navigating in unknown environmen...
Sam T. Roweis, Ruslan Salakhutdinov