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» Approximating Parameterized Convex Optimization Problems
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ECCV
2008
Springer
14 years 7 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»
13 years 5 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
13 years 11 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
TWC
2010
13 years 5 days 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»
13 years 5 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