docs/algorithms-bibliography.md - systemds - Git at Google

 ---
 layout: global
 title: SystemML Algorithms Reference - Bibliography
 displayTitle: <a href="algorithms-reference.html">SystemML Algorithms Reference</a>
 ---
 <!--
 {% comment %}
 Licensed to the Apache Software Foundation (ASF) under one or more
 contributor license agreements.  See the NOTICE file distributed with
 this work for additional information regarding copyright ownership.
 The ASF licenses this file to you under the Apache License, Version 2.0
 (the "License"); you may not use this file except in compliance with
 the License.  You may obtain a copy of the License at

 http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
 {% endcomment %}
 -->

 # 7. Bibliography

 **[AcockStavig1979]** 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.

 **[AgrawalKSX2002]** 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.

 **[Agresti2002]** Alan Agresti, Categorical
 Data Analysis, Second Edition, Wiley Series in
 Probability and Statistics, Wiley-Interscience
 2002, 710.

 **[AloiseDHP2009]** 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.

 **[ArthurVassilvitskii2007]**
 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.

 **[Breiman2001]** L. Breiman. Random forests. Machine Learning, 45(1):5–32, 2001.

 **[BreimanFOS1984]** L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification and Regression Trees. Wadsworth, 1984.

 **[Chapelle2007]** Olivier Chapelle, Training a Support Vector Machine in the Primal, Neural Computation, 2007.

 **[Cochran1954]** William G. Cochran,
 Some Methods for Strengthening the Common $\chi^2$ Tests,
 Biometrics, Volume 10, Number 4, December
 1954, 417--451.

 **[Collett2003]** D. Collett. Modelling Survival Data in Medical Research, Second Edition. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis, 2003.

 **[Gill2000]** 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.

 **[Hartigan1975]** John A. Hartigan,
 Clustering Algorithms, John Wiley~&~Sons Inc.,
 Probability and Mathematical Statistics, April
 1975, 365.

 **[Hsieh2008]** 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.

 **[Lin2008]** 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.

 **[McCallum1998]** A. McCallum and K. Nigam, A comparison of event models for naive bayes text classification, AAAI-98 workshop on learning for text categorization, 1998.

 **[McCullagh1989]** Peter McCullagh and John Ashworth
 Nelder, Generalized Linear Models, Second Edition,
 Monographs on Statistics and Applied Probability, Number 37,
 1989, Chapman & Hall/CRC, 532.

 **[Nelder1972]** 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.

 **[Nocedal1999]** J. Nocedal and S. J. Wright, Numerical Optimization, Springer-Verlag, 1999.

 **[Nocedal2006]** Optimization Numerical Optimization,
 Jorge Nocedal and Stephen Wright, Springer Series
 in Operations Research and Financial Engineering, 664,
 Second Edition, Springer, 2006.

 **[PandaHBB2009]** 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.

 **[Russell2009]** S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, 2009.

 **[Scholkopf1995]** B. Scholkopf, C. Burges and V. Vapnik, Extracting Support Data for a Given Task, International Conference on Knowledge Discovery and Data Mining (ICDM), 1995.

 **[Stevens1946]** Stanley Smith Stevens,
 On the Theory of Scales of Measurement, Science
 June 7, 1946, Volume 103, Number 2684,
 677--680.

 **[Vetterling1992]**
 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.

 **[ZhouWSP08]**
 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.
	---
	layout: global
	title: SystemML Algorithms Reference - Bibliography
	displayTitle: <a href="algorithms-reference.html">SystemML Algorithms Reference</a>
	---
	<!--
	{% comment %}
	Licensed to the Apache Software Foundation (ASF) under one or more
	contributor license agreements. See the NOTICE file distributed with
	this work for additional information regarding copyright ownership.
	The ASF licenses this file to you under the Apache License, Version 2.0
	(the "License"); you may not use this file except in compliance with
	the License. You may obtain a copy of the License at

	http://www.apache.org/licenses/LICENSE-2.0

	Unless required by applicable law or agreed to in writing, software
	distributed under the License is distributed on an "AS IS" BASIS,
	WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	See the License for the specific language governing permissions and
	limitations under the License.
	{% endcomment %}
	-->

	# 7. Bibliography

	[AcockStavig1979] 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.

	[AgrawalKSX2002] 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.

	[Agresti2002] Alan Agresti, Categorical
	Data Analysis, Second Edition, Wiley Series in
	Probability and Statistics, Wiley-Interscience
	2002, 710.

	[AloiseDHP2009] 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.

	[ArthurVassilvitskii2007]
	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.

	[Breiman2001] L. Breiman. Random forests. Machine Learning, 45(1):5–32, 2001.

	[BreimanFOS1984] L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification and Regression Trees. Wadsworth, 1984.

	[Chapelle2007] Olivier Chapelle, Training a Support Vector Machine in the Primal, Neural Computation, 2007.

	[Cochran1954] William G. Cochran,
	Some Methods for Strengthening the Common $\chi^2$ Tests,
	Biometrics, Volume 10, Number 4, December
	1954, 417--451.

	[Collett2003] D. Collett. Modelling Survival Data in Medical Research, Second Edition. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis, 2003.

	[Gill2000] 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.

	[Hartigan1975] John A. Hartigan,
	Clustering Algorithms, John Wiley~&~Sons Inc.,
	Probability and Mathematical Statistics, April
	1975, 365.

	[Hsieh2008] 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.

	[Lin2008] 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.

	[McCallum1998] A. McCallum and K. Nigam, A comparison of event models for naive bayes text classification, AAAI-98 workshop on learning for text categorization, 1998.

	[McCullagh1989] Peter McCullagh and John Ashworth
	Nelder, Generalized Linear Models, Second Edition,
	Monographs on Statistics and Applied Probability, Number 37,
	1989, Chapman & Hall/CRC, 532.

	[Nelder1972] 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.

	[Nocedal1999] J. Nocedal and S. J. Wright, Numerical Optimization, Springer-Verlag, 1999.

	[Nocedal2006] Optimization Numerical Optimization,
	Jorge Nocedal and Stephen Wright, Springer Series
	in Operations Research and Financial Engineering, 664,
	Second Edition, Springer, 2006.

	[PandaHBB2009] 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.

	[Russell2009] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, 2009.

	[Scholkopf1995] B. Scholkopf, C. Burges and V. Vapnik, Extracting Support Data for a Given Task, International Conference on Knowledge Discovery and Data Mining (ICDM), 1995.

	[Stevens1946] Stanley Smith Stevens,
	On the Theory of Scales of Measurement, Science
	June 7, 1946, Volume 103, Number 2684,
	677--680.

	[Vetterling1992]
	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.

	[ZhouWSP08]
	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.