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By Raymond Hill

ISBN-10: 0001000101

ISBN-13: 9780001000100

ISBN-10: 0198538030

ISBN-13: 9780198538035

ISBN-10: 0198596170

ISBN-13: 9780198596172

ISBN-10: 9876543210

ISBN-13: 9789876543217

Algebraic coding idea is a brand new and quickly constructing topic, well known for its many functional purposes and for its fascinatingly wealthy mathematical constitution. This e-book presents an easy but rigorous creation to the speculation of error-correcting codes. according to classes given by way of the writer over numerous years to complicated undergraduates and first-year graduated scholars, this advisor encompasses a huge variety of routines, all with ideas, making the booklet hugely compatible for person research

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93 (19), 96–109 (2013) 29. : A precise hard-cut EM algorithm for mixtures of Gaussian processes. , Wang, L. ) ICIC 2014. LNCS, vol. 8589, pp. 68–75. Springer, Heidelberg (2014) 30. : Gaussian Processes for Machine Learning. MIT Press, Cambridge (2006) 31. : Predictive approaches for choosing hyperparameters in Gaussian processes. Neural Comput. 13(5), 1103–1118 (2001) 32. : A unifying view of sparse approximate Gaussian process regression. J. Mach. Learn. Res. 6, 1935–1959 (2005) 33. : Sparse online Gaussian processes.

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Overlapping mixtures of Gaussian processes for the data association problem. Pattern Recogn. 45(4), 1386–1395 (2012) 26. : An efficient EM approach to parameter learning of the mixture of Gaussian processes. , He, H. ) ISNN 2011, Part II. LNCS, vol. 6676, pp. 165–174. Springer, Heidelberg (2011) 27. : Markov logic mixtures of Gaussian processes: towards machines reading regression data. In: Proceedings of the 15th International Conference on Artificial Intelligence and Statistics, JMLR:W&CP, vol.

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A first course in coding theory by Raymond Hill


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