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» Approximating Parameterized Convex Optimization Problems
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ECCV
2008
Springer
16 years 1 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
SIGMETRICS
2010
ACM
193views Hardware» more  SIGMETRICS 2010»
14 years 11 months ago
Distributed caching over heterogeneous mobile networks
Sharing content over a mobile network through opportunistic contacts has recently received considerable attention. In proposed scenarios, users store content they download in a lo...
Stratis Ioannidis, Laurent Massoulié, Augus...
IJCNN
2007
IEEE
15 years 6 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
122
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TWC
2010
14 years 6 months ago
Distributed consensus-based demodulation: algorithms and error analysis
This paper deals with distributed demodulation of space-time transmissions of a common message from a multiantenna access point (AP) to a wireless sensor network. Based on local me...
Hao Zhu, Alfonso Cano, Georgios B. Giannakis
SIGPRO
2002
160views more  SIGPRO 2002»
14 years 11 months ago
New multiscale transforms, minimum total variation synthesis: applications to edge-preserving image reconstruction
This paper describes newly invented multiscale transforms known under the name of the ridgelet [6] and the curvelet transforms [9, 8]. These systems combine ideas of multiscale an...
Emmanuel J. Candès, Franck Guo