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» Using Gaussian Processes to Optimize Expensive Functions
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CVPR
2009
IEEE
15 years 2 months ago
Nonrigid Shape Recovery by Gaussian Process Regression
Most state-of-the-art nonrigid shape recovery methods usually use explicit deformable mesh models to regularize surface deformation and constrain the search space. These triangu...
Jianke Zhu, Michael R. Lyu, Steven C. H. Hoi
RSS
2007
176views Robotics» more  RSS 2007»
13 years 9 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
ICA
2007
Springer
14 years 1 months ago
A Robust Complex FastICA Algorithm Using the Huber M-Estimator Cost Function
In this paper, we propose to use the Huber M-estimator cost function as a contrast function within the complex FastICA algorithm of Bingham and Hyvarinen for the blind separation o...
Jih-Cheng Chao, Scott C. Douglas
ICA
2004
Springer
14 years 28 days ago
Blind Deconvolution Using the Relative Newton Method
We propose a relative optimization framework for quasi maximum likelihood blind deconvolution and the relative Newton method as its particular instance. Special Hessian structure a...
Alexander M. Bronstein, Michael M. Bronstein, Mich...
EOR
2008
150views more  EOR 2008»
13 years 7 months ago
Portfolio optimization when asset returns have the Gaussian mixture distribution
Abstract. Portfolios of assets whose returns have the Gaussian mixture distribution are optimized in the static setting to find portfolio weights and efficient frontiers using the ...
Ian Buckley, David Saunders, Luis Seco