Books on the topic 'Machine learning, Global Optimization'

Optimization for machine learning. Cambridge, Mass: MIT Press, 2012.

Lin, Zhouchen, Huan Li, and Cong Fang. Accelerated Optimization for Machine Learning. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2910-8.

Agrawal, Tanay. Hyperparameter Optimization in Machine Learning. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6579-6.

Fazelnia, Ghazal. Optimization for Probabilistic Machine Learning. [New York, N.Y.?]: [publisher not identified], 2019.

Nicosia, Giuseppe, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Giorgio Jansen, Panos M. Pardalos, Giovanni Giuffrida, and Renato Umeton, eds. Machine Learning, Optimization, and Data Science. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95470-3.

Nicosia, Giuseppe, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Giorgio Jansen, Panos M. Pardalos, Giovanni Giuffrida, and Renato Umeton, eds. Machine Learning, Optimization, and Data Science. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95467-3.

Jiang, Jiawei, Bin Cui, and Ce Zhang. Distributed Machine Learning and Gradient Optimization. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-3420-8.

Pardalos, Panos, Mario Pavone, Giovanni Maria Farinella, and Vincenzo Cutello, eds. Machine Learning, Optimization, and Big Data. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27926-8.

Nicosia, Giuseppe, Panos Pardalos, Renato Umeton, Giovanni Giuffrida, and Vincenzo Sciacca, eds. Machine Learning, Optimization, and Data Science. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37599-7.

Kulkarni, Anand J., and Suresh Chandra Satapathy, eds. Optimization in Machine Learning and Applications. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0994-0.

Nicosia, Giuseppe, Panos Pardalos, Giovanni Giuffrida, Renato Umeton, and Vincenzo Sciacca, eds. Machine Learning, Optimization, and Data Science. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13709-0.

Nicosia, Giuseppe, Panos Pardalos, Giovanni Giuffrida, and Renato Umeton, eds. Machine Learning, Optimization, and Big Data. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72926-8.

Nicosia, Giuseppe, Varun Ojha, Emanuele La Malfa, Giorgio Jansen, Vincenzo Sciacca, Panos Pardalos, Giovanni Giuffrida, and Renato Umeton, eds. Machine Learning, Optimization, and Data Science. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64580-9.

Nicosia, Giuseppe, Varun Ojha, Emanuele La Malfa, Giorgio Jansen, Vincenzo Sciacca, Panos Pardalos, Giovanni Giuffrida, and Renato Umeton, eds. Machine Learning, Optimization, and Data Science. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64583-0.

Pardalos, Panos M., Piero Conca, Giovanni Giuffrida, and Giuseppe Nicosia, eds. Machine Learning, Optimization, and Big Data. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-51469-7.

Joshi, Gauri. Optimization Algorithms for Distributed Machine Learning. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19067-4.

Gupta, Punit, Mayank Kumar Goyal, Sudeshna Chakraborty, and Ahmed A. Elngar. Machine Learning and Optimization Models for Optimization in Cloud. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003185376.

Jain, Vishal, Sapna Juneja, Abhinav Juneja, and Ramani Kannan. Handbook of Machine Learning for Computational Optimization. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003138020.

Aggarwal, Charu C. Linear Algebra and Optimization for Machine Learning. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40344-7.

Dunn, Jack (Jack William), author, ed. Machine learning under a modern optimization lens. Belmont, Massachusetts: Dynamic Ideas LLC, 2019.

Li, Fengpei. Stochastic Methods in Optimization and Machine Learning. [New York, N.Y.?]: [publisher not identified], 2021.

Poznyak, Alexander S. Learning automata and stochastic optimization. Berlin: Springer, 1997.

K, Najim, ed. Learning automata and stochastic optimization. Berlin: Springer, 1997.

Genetic algorithms in search, optimization, and machine learning. Reading, Mass: Addison-Wesley Pub. Co., 1989.

Lan, Guanghui. First-order and Stochastic Optimization Methods for Machine Learning. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39568-1.

Shi, Kevin. Cryptographic approaches to security and optimization in machine learning. [New York, N.Y.?]: [publisher not identified], 2020.

Sakr, Nourhan. Data-Driven Combinatorial Optimization and Efficient Machine Learning Frameworks. [New York, N.Y.?]: [publisher not identified], 2019.

Birattari, Mauro. Tuning Metaheuristics: A Machine Learning Perspective. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

Pardalos, Panos M., Varvara Rasskazova, and Michael N. Vrahatis, eds. Black Box Optimization, Machine Learning, and No-Free Lunch Theorems. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66515-9.

Pardalos, Panos M., Stamatina Th Rassia, and Arsenios Tsokas, eds. Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84459-2.

Kiranyaz, Serkan, Turker Ince, and Moncef Gabbouj. Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-37846-1.

Optimization Algorithms for Structured Machine Learning and Image Processing Problems. [New York, N.Y.?]: [publisher not identified], 2013.

Chelouah, Rachid, and Patrick Siarry. Optimization and Machine Learning: Optimization for Machine Learning and Machine Learning for Optimization. Wiley & Sons, Incorporated, John, 2022.

Chelouah, Rachid, and Patrick Siarry. Optimization and Machine Learning: Optimization for Machine Learning and Machine Learning for Optimization. Wiley & Sons, Incorporated, John, 2022.

Chelouah, Rachid, and Patrick Siarry. Optimization and Machine Learning: Optimization for Machine Learning and Machine Learning for Optimization. Wiley & Sons, Incorporated, John, 2022.

Chelouah, Rachid, and Patrick Siarry. Optimization and Machine Learning: Optimization for Machine Learning and Machine Learning for Optimization. Wiley & Sons, Incorporated, John, 2022.

Wright, Stephen J., Sebastian Nowozin, and Suvrit Sra. Optimization for Machine Learning. MIT Press, 2019.

Sra, Suvrit, Sebastian Nowozin, and Stephen J. Wright, eds. Optimization for Machine Learning. The MIT Press, 2011. http://dx.doi.org/10.7551/mitpress/8996.001.0001.

Wright, Stephen J., Sebastian Nowozin, and Suvrit Sra. Optimization for Machine Learning. MIT Press, 2011.

Wright, Stephen J., Sebastian Nowozin, Suvrit Sra, and Suvrit Sra. Optimization for Machine Learning. MIT Press, 2011.

Suh, Changho. Convex Optimization for Machine Learning. Now Publishers, 2022.

Kar, Purushottam, and Prateek Jain. Non-convex Optimization for Machine Learning. Now Publishers Inc, 2018.

Satapathy, Suresh Chandra, and Anand J. Kulkarni. Optimization in Machine Learning and Applications. Springer, 2019.

Satapathy, Suresh Chandra, and Anand J. Kulkarni. Optimization in Machine Learning and Applications. Springer, 2019.

Distributed Machine Learning and Gradient Optimization. Springer Singapore Pte. Limited, 2021.

Satapathy, Suresh Chandra, and Anand J. Kulkarni. Optimization in Machine Learning and Applications. Springer Singapore Pte. Limited, 2020.

Theodoridis, Sergios. Machine Learning. Elsevier Science & Technology Books, 2020.

Gupta, Punit. Machine Learning and Optimization Models for Optimization in Cloud. CRC Press LLC, 2022.

Gupta, Punit, Ahmed A. Elngar, Mayank Kumar Goyal, and Sudeshna Chakraborty. Machine Learning and Optimization Models for Optimization in Cloud. Taylor & Francis Group, 2022.

Machine Learning and Optimization Models for Optimization in Cloud. Taylor & Francis Group, 2022.