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| <h1 class="title"><a href="algorithms-reference.html">SystemML Algorithms Reference</a></h1> |
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| <h1 id="bibliography">7. Bibliography</h1> |
| |
| <p><strong>[AcockStavig1979]</strong> Alan C. Acock and Gordon |
| R. Stavig, A Measure of Association for Nonparametric |
| Statistics, Social Forces, Oxford University |
| Press, Volume 57, Number 4, June, 1979, |
| 1381–1386.</p> |
| |
| <p><strong>[AgrawalKSX2002]</strong> Rakesh Agrawal and |
| Jerry Kiernan and Ramakrishnan Srikant and Yirong Xu, |
| Hippocratic Databases, Proceedings of the 28-th |
| International Conference on Very Large Data Bases (VLDB 2002), |
| Hong Kong, China, August 20–23, 2002, |
| 143–154.</p> |
| |
| <p><strong>[Agresti2002]</strong> Alan Agresti, Categorical |
| Data Analysis, Second Edition, Wiley Series in |
| Probability and Statistics, Wiley-Interscience |
| 2002, 710.</p> |
| |
| <p><strong>[AloiseDHP2009]</strong> Daniel Aloise and Amit |
| Deshpande and Pierre Hansen and Preyas Popat, NP-hardness of |
| Euclidean Sum-of-squares Clustering, Machine Learning, |
| Kluwer Academic Publishers, Volume 75, Number 2, |
| May, 2009, 245–248.</p> |
| |
| <p><strong>[ArthurVassilvitskii2007]</strong> |
| k-means++: The Advantages of Careful Seeding, David |
| Arthur and Sergei Vassilvitskii, Proceedings of the 18th |
| Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2007), |
| January 7–9, 2007, New Orleans, LA, |
| USA, 1027–1035.</p> |
| |
| <p><strong>[Breiman2001]</strong> L. Breiman. Random forests. Machine Learning, 45(1):5–32, 2001.</p> |
| |
| <p><strong>[BreimanFOS1984]</strong> L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification and Regression Trees. Wadsworth, 1984.</p> |
| |
| <p><strong>[Chapelle2007]</strong> Olivier Chapelle, Training a Support Vector Machine in the Primal, Neural Computation, 2007.</p> |
| |
| <p><strong>[Cochran1954]</strong> William G. Cochran, |
| Some Methods for Strengthening the Common $\chi^2$ Tests, |
| Biometrics, Volume 10, Number 4, December |
| 1954, 417–451.</p> |
| |
| <p><strong>[Collett2003]</strong> D. Collett. Modelling Survival Data in Medical Research, Second Edition. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis, 2003.</p> |
| |
| <p><strong>[Gill2000]</strong> Jeff Gill, Generalized Linear |
| Models: A Unified Approach, Sage University Papers Series on |
| Quantitative Applications in the Social Sciences, Number 07-134, |
| 2000, Sage Publications, 101.</p> |
| |
| <p><strong>[Hartigan1975]</strong> John A. Hartigan, |
| Clustering Algorithms, John Wiley~&~Sons Inc., |
| Probability and Mathematical Statistics, April |
| 1975, 365.</p> |
| |
| <p><strong>[Hsieh2008]</strong> C-J Hsieh, K-W Chang, C-J Lin, S. S. Keerthi and S. Sundararajan, A Dual Coordinate Descent Method for Large-scale Linear SVM, International Conference of Machine Learning (ICML), 2008.</p> |
| |
| <p><strong>[Lin2008]</strong> Chih-Jen Lin and Ruby C. Weng and |
| S. Sathiya Keerthi, Trust Region Newton Method for |
| Large-Scale Logistic Regression, Journal of Machine Learning |
| Research, April, 2008, Volume 9, 627–650.</p> |
| |
| <p><strong>[McCallum1998]</strong> A. McCallum and K. Nigam, A comparison of event models for naive bayes text classification, AAAI-98 workshop on learning for text categorization, 1998.</p> |
| |
| <p><strong>[McCullagh1989]</strong> Peter McCullagh and John Ashworth |
| Nelder, Generalized Linear Models, Second Edition, |
| Monographs on Statistics and Applied Probability, Number 37, |
| 1989, Chapman & Hall/CRC, 532.</p> |
| |
| <p><strong>[Nelder1972]</strong> John Ashworth Nelder and Robert |
| William Maclagan Wedderburn, Generalized Linear Models, |
| Journal of the Royal Statistical Society, Series A |
| (General), 1972, Volume 135, Number 3, |
| 370–384.</p> |
| |
| <p><strong>[Nocedal1999]</strong> J. Nocedal and S. J. Wright, Numerical Optimization, Springer-Verlag, 1999.</p> |
| |
| <p><strong>[Nocedal2006]</strong> Optimization Numerical Optimization, |
| Jorge Nocedal and Stephen Wright, Springer Series |
| in Operations Research and Financial Engineering, 664, |
| Second Edition, Springer, 2006.</p> |
| |
| <p><strong>[PandaHBB2009]</strong> B. Panda, J. Herbach, S. Basu, and R. J. Bayardo. PLANET: massively parallel learning of tree ensembles with mapreduce. PVLDB, 2(2):1426– 1437, 2009.</p> |
| |
| <p><strong>[Russell2009]</strong> S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, 2009.</p> |
| |
| <p><strong>[Scholkopf1995]</strong> B. Scholkopf, C. Burges and V. Vapnik, Extracting Support Data for a Given Task, International Conference on Knowledge Discovery and Data Mining (ICDM), 1995.</p> |
| |
| <p><strong>[Stevens1946]</strong> Stanley Smith Stevens, |
| On the Theory of Scales of Measurement, Science |
| June 7, 1946, Volume 103, Number 2684, |
| 677–680.</p> |
| |
| <p><strong>[Vetterling1992]</strong> |
| W. T. Vetterling and B. P. Flannery, |
| Multidimensions in Numerical Recipes in C - The Art in Scientific Computing, W. H. Press and S. A. Teukolsky (eds.), Cambridge University Press, 1992.</p> |
| |
| <p><strong>[ZhouWSP08]</strong> |
| Y. Zhou, D. M. Wilkinson, R. Schreiber, and R. Pan. Large-scale parallel collaborative filtering for the Netflix prize. |
| In Algorithmic Aspects in Information and Management, 4th International Conference, AAIM 2008, Shanghai, China, June 23-25, 2008. Proceedings, pages 337–348, 2008.</p> |
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