Smoothing Alternating Direction Methods for Fully Nonsmooth Constrained Convex Optimization
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One of the key trends in computing over the past two decades has been increased distribution, both at the processor level, where multi-core architectures are now the norm, and at the system level, where many key services are currently distributed overmulti ...
We introduce a new wavelet-based method for the implementation of Total-Variation-type denoising. The data term is least-squares, while the regularization term is gradient-based. The particularity of our method is to exploit a link between the discrete gra ...
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Location finding for CDMA subscribers using an antenna array at the base station is studied. Two methods are considered for radio location that are based on time of arrival (TOA) and angle of arrival (AOA) measurements. For TOA estimates, a maximum likelih ...
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We show that we can effectively fit arbitrarily complex animation models to noisy data extracted from ordinary face images. Our approach is based on least-squares adjustment, using of a set of progressively finer control triangulations and takes advantage ...
The article describes recent adaptive estimation algorithms over distributed networks. The algorithms rely on local collaborations and exploit the space-time structure of the data. Each node is allowed to communicate with its neighbors in order to exploit ...
The Institute of Electronics, Information and Communication Engineers2007
We provide an overview of adaptive estimation algorithms over
distributed networks. The algorithms rely on local collaborations and exploit the space-time structure of the data. Each node is allowed to communicate with its neighbors in order to exploit th ...