Publications about 'convex optimization problem'

Articles in journal or book chapters

1. E.J. Candes and Y. Plan. Matrix Completion With Noise. Proceedings of the IEEE, 98(6):925-936, june 2010. Keyword(s): compressed sensing, convex optimization problem, data constraints, low rank matrices, matrix completion, nuclear norm minimization, data integrity, matrix algebra, minimisation, noise, signal sampling;. [Abstract] [bibtex-entry]



2. E.J. Candes, J. Romberg, and T. Tao. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory, 52(2):489-509, feb. 2006. Keyword(s): Fourier coefficient, convex optimization, discrete-time signal, image reconstruction, incomplete frequency information, linear programming, minimization problem, nonlinear sampling theorem, piecewise constant object, probability value, robust uncertainty principle, signal reconstruction, sparse random matrix, trigonometric expansion, Fourier analysis, convex programming, image reconstruction, image sampling, indeterminancy, linear programming, minimisation, piecewise constant techniques, probability, signal reconstruction, signal sampling, sparse matrices;. [Abstract] [bibtex-entry]



3. E.J. Candes and T. Tao. Decoding by linear programming. IEEE Transactions on Information Theory, 51(12):4203-4215, December 2005. Keyword(s): Gaussian random matrix, basis pursuit, linear code decoding, linear programming, minimization problem, natural error correcting problem, simple convex optimization problem, sparse solution, uncertainty principle, Gaussian processes, convex programming, decoding, error correction codes, indeterminancy, linear codes, linear programming, minimisation, random codes, sparse matrices;. [Abstract] [bibtex-entry]

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