Bibliography

For more information about algorithms implemented in oneDAL, refer to the following publications:

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Adams, Robert A., and John JF Fournier. Sobolev spaces. Vol. 140. Elsevier, 2003

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Rakesh Agrawal, Ramakrishnan Srikant. Fast Algorithms for Mining Association Rules. Proceedings of the 20th VLDB Conference Santiago, Chile, 1994.

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Jerome Friedman, Trevor Hastie, and Robert Tibshirani. Additive Logistic regression: a statistical view of boosting. The Annals of Statistics, 28(2), pp: 337-407, 2000.

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Friedman, Jerome, Trevor Hastie, and Rob Tibshirani. Regularization paths for generalized linear models via coordinate descent.. Journal of statistical software 33.1 (2010): 1.

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Jerome Friedman, Trevor Hastie, Robert Tibshirani. 2017. The Elements of Statistical Learning Data Mining, Inference, and Prediction. Springer.

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Gareth James, Daniela Witten, Trevor Hastie, and Rob Tibshirani. An Introduction to Statistical Learning with Applications in R. Springer Series in Statistics, Springer, 2013 (Corrected at 6th printing 2015).

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Thorsten Joachims. Making Large-Scale SVM Learning Practical. Advances in Kernel Methods - Support Vector Learning, B. Schölkopf, C. Burges, and A. Smola (ed.), pp: 169 – 184, MIT Press Cambridge, MA, USA 1999.

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Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter Sadowski, Evan Racah, Suren Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey. PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures, 2016. Available from https://arxiv.org/abs/1607.08220.

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Platt, John. “Sequential minimal optimization: A fast algorithm for training support vector machines.” (1998). Available from https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/tr-98-14.pdf.

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Michael Sutton, Tal Ben-Nun, Amnon Barak. Optimizing Parallel Graph Connectivity Computation via Subgraph Sampling. Symposium on Parallel and Distributed Processing, IPDPS 2018.

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Verma, Deepika, Namita Kakkar, and Neha Mehan. “Comparison of brute-force and KD tree algorithm.” International Journal of Advanced Research in Computer and Communication Engineering 3, no. 1 (2014): 5291-5294.

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Wen, Zeyi, Jiashuai Shi, Qinbin Li, Bingsheng He, and Jian Chen. ThunderSVM: A fast SVM library on GPUs and CPUs. The Journal of Machine Learning Research, 19, 1-5 (2018).

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Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng. Probability Estimates for Multi-class Classification by Pairwise Coupling. Journal of Machine Learning Research 5, pp: 975-1005, 2004.

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Zhu, Ji, Hui Zou, Saharon Rosset and Trevor J. Hastie. Multi-class AdaBoost. 2005