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v2010.10.26 - Convex Optimization

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796 BIBLIOGRAPHY[116] Bruce Randall Donald. 3-D structure in chemistry and molecular biology, 1998.http://www.cs.duke.edu/brd/Teaching/Previous/Bio[117] David L. Donoho. Neighborly polytopes and sparse solution of underdeterminedlinear equations. Technical Report 2005-04, Stanford University, Department ofStatistics, January 2005.www-stat.stanford.edu/~donoho/Reports/2005/NPaSSULE-01-28-05.pdf[118] David L. Donoho. Compressed sensing. IEEE Transactions on Information Theory,52(4):1289–1306, April 2006.www-stat.stanford.edu/~donoho/Reports/2004/CompressedSensing091604.pdf[119] David L. Donoho. High-dimensional centrally symmetric polytopes withneighborliness proportional to dimension. Discrete & Computational Geometry,35(4):617–652, May 2006.[120] David L. Donoho, Michael Elad, and Vladimir Temlyakov. Stable recovery ofsparse overcomplete representations in the presence of noise. IEEE Transactionson Information Theory, 52(1):6–18, January 2006.www-stat.stanford.edu/~donoho/Reports/2004/StableSparse-Donoho-etal.pdf[121] David L. Donoho and Philip B. Stark. Uncertainty principles and signal recovery.SIAM Journal on Applied Mathematics, 49(3):906–931, June 1989.[122] David L. Donoho and Jared Tanner. Neighborliness of randomly projectedsimplices in high dimensions. Proceedings of the National Academy of Sciences,102(27):9452–9457, July 2005.[123] David L. Donoho and Jared Tanner. Sparse nonnegative solution of underdeterminedlinear equations by linear programming. Proceedings of the National Academy ofSciences, 102(27):9446–9451, July 2005.[124] David L. Donoho and Jared Tanner. Counting faces of randomly projectedpolytopes when the projection radically lowers dimension. Journal of the AmericanMathematical Society, 22(1):1–53, January 2009.[125] Miguel Nuno Ferreira Fialho dos Anjos. New <strong>Convex</strong> Relaxations for the MaximumCut and VLSI Layout Problems. PhD thesis, University of Waterloo, OntarioCanada, Department of Combinatorics and <strong>Optimization</strong>, 2001.http://etd.uwaterloo.ca/etd/manjos2001.pdf[126] John Duchi, Shai Shalev-Shwartz, Yoram Singer, and Tushar Chandra. Efficientprojections onto the l 1 -ball for learning in high dimensions. In Proceedings ofthe 25 th International Conference on Machine Learning (ICML), pages 272–279,Helsinki Finland, July 2008. Association for Computing Machinery (ACM).http://icml2008.cs.helsinki.fi/papers/361.pdf[127] Richard L. Dykstra. An algorithm for restricted least squares regression. Journal ofthe American Statistical Association, 78(384):837–842, 1983.[128] Peter J. Eccles. An Introduction to Mathematical Reasoning: numbers, sets andfunctions. Cambridge University Press, 1997.

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