Books on the topic 'Learning algorithms'

Celebi, M. Emre, and Kemal Aydin, eds. Unsupervised Learning Algorithms. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24211-8.

Li, Fuwei, Lifeng Lai, and Shuguang Cui. Machine Learning Algorithms. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16375-3.

Szepesvári, Csaba. Algorithms for Reinforcement Learning. Cham: Springer International Publishing, 2010. http://dx.doi.org/10.1007/978-3-031-01551-9.

Ayyadevara, V. Kishore. Pro Machine Learning Algorithms. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3564-5.

Szepesvári, Csaba. Algorithms for reinforcement learning. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2010.

Hutchinson, Alan. Algorithmic learning. Oxford: Clarendon Press, 1994.

Learning kernel classifiers: Theory and algorithms. Cambridge, Mass: MIT Press, 2002.

The design and analysis of efficient learning algorithms. Cambridge, Mass: MIT Press, 1992.

Schapire, Robert E. Boosting: Foundations and algorithms. Cambridge, MA: MIT Press, 2012.

Pereira, Ana I., Florbela P. Fernandes, João P. Coelho, João P. Teixeira, Maria F. Pacheco, Paulo Alves, and Rui P. Lopes, eds. Optimization, Learning Algorithms and Applications. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91885-9.

Dawid, Herbert. Adaptive Learning by Genetic Algorithms. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-00211-7.

Grefenstette, John J., ed. Genetic Algorithms for Machine Learning. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2740-4.

Pedrycz, Witold, and Shyi-Ming Chen, eds. Deep Learning: Algorithms and Applications. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-31760-7.

Mandal, Jyotsna Kumar, Somnath Mukhopadhyay, Paramartha Dutta, and Kousik Dasgupta, eds. Algorithms in Machine Learning Paradigms. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1041-0.

Dumitrescu, Bogdan, and Paul Irofti. Dictionary Learning Algorithms and Applications. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78674-2.

Dawid, Herbert. Adaptive Learning by Genetic Algorithms. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-18142-9.

Pereira, Ana I., Andrej Košir, Florbela P. Fernandes, Maria F. Pacheco, João P. Teixeira, and Rui P. Lopes, eds. Optimization, Learning Algorithms and Applications. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-23236-7.

J, Grefenstette John, ed. Genetic algorithms for machine learning. Boston: Kluwer Academic Publishers, 1994.

MACKAY, DAVID J. C. Information Theory, Inference & Learning Algorithms. Cambridge, UK: Cambridge University Press, 2003.

Paliouras, Georgios. Scalability of machine learning algorithms. Manchester: University of Manchester, 1993.

Grefenstette, John J. Genetic Algorithms for Machine Learning. Boston, MA: Springer US, 1994.

Salakhutdinov, Ruslan. Efficient optimization algorithms for learning. Ottawa: National Library of Canada, 2003.

Pereira, Ana I., Armando Mendes, Florbela P. Fernandes, Maria F. Pacheco, João P. Coelho, and José Lima, eds. Optimization, Learning Algorithms and Applications. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53025-8.

Pereira, Ana I., Armando Mendes, Florbela P. Fernandes, Maria F. Pacheco, João P. Coelho, and José Lima, eds. Optimization, Learning Algorithms and Applications. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53036-4.

Kuan, C. M. Convergence of learning algorithms with constant learning rates. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1990.

1941-, Arikawa S., ed. Algorithmic learning theory. Berlin: Springer, 1990.

1967-, Thrun Sebastian, and Pratt Lorien, eds. Learning to learn. Boston, Mass: Kluwer Academic Publishers, 1998.

Analysis of algorithms: An active learning approach. 2nd ed. Sudbury, Mass: Jones and Bartlett Publishers, 2008.

Zhang, Yi, and Zhou Jiliu, eds. Subspace learning of neural networks. Boca Raton: CRC Press, 2011.

Raj Chelliah, Pethuru, Usha Sakthivel, and Nagarajan Susila. Applied Learning Algorithms for Intelligent IoT. Boca Raton: Auerbach Publications, 2021. http://dx.doi.org/10.1201/9781003119838.

Chatterjee, Chanchal. Adaptive Machine Learning Algorithms with Python. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8017-1.

Belousov, Boris, Hany Abdulsamad, Pascal Klink, Simone Parisi, and Jan Peters, eds. Reinforcement Learning Algorithms: Analysis and Applications. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-41188-6.

Das, Santosh Kumar, Shom Prasad Das, Nilanjan Dey, and Aboul-Ella Hassanien, eds. Machine Learning Algorithms for Industrial Applications. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-50641-4.

Li, Jun-Bao, Shu-Chuan Chu, and Jeng-Shyang Pan. Kernel Learning Algorithms for Face Recognition. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-0161-2.

Wang, Huiwei, Huaqing Li, and Bo Zhou. Distributed Optimization, Game and Learning Algorithms. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4528-7.

Mars, Phil, J. R. Chen, and Raghu Nambiar. Learning Algorithms. CRC Press, 2018. http://dx.doi.org/10.1201/9781351073974.

Learning Algorithms. Taylor & Francis Group, 2017.

Mohammed, Mohssen, Muhammad Badruddin Khan, and Eihab Bashier Mohammed Bashier. Machine Learning. Taylor & Francis Group, 2020.

Celebi, M. Emre, and Kemal Aydin. Unsupervised Learning Algorithms. Springer, 2018.

Celebi, M. Emre, and Kemal Aydin. Unsupervised Learning Algorithms. Springer London, Limited, 2016.

Unsupervised Learning Algorithms. Springer, 2016.

Gacovski, Zoran. Deep Learning Algorithms. Arcler Education Inc, 2021.

Mohammed, Mohssen, Muhammad Badruddin Khan, and Eihab Bashier Mohammed Bashier. Machine Learning: Algorithms and Applications. Taylor & Francis Group, 2016.

Mohammed, Mohssen, Muhammad Badruddin Khan, and Eihab Bashier Mohammed Bashier. Machine Learning: Algorithms and Applications. Taylor & Francis Group, 2016.

Machine Learning: Algorithms and Applications. Taylor & Francis Group, 2016.

Szepesvari, Csaba. Algorithms for Reinforcement Learning. Morgan & Claypool Publishers, 2010.

Grossi, Csaba. Algorithms for Reinforcement Learning. Springer International Publishing AG, 2010.

Bach, Francis, Yoav Freund, and Robert E. Schapire. Boosting: Foundations and Algorithms. MIT Press, 2012.

Freund, Yoav, and Robert E. Schapire. Boosting: Foundations and Algorithms. MIT Press, 2018.

Bach, Francis, Yoav Freund, and Robert E. Schapire. Boosting: Foundations and Algorithms. MIT Press, 2014.