Libros sobre el tema "Machine learning, Global Optimization"

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

Lin, Zhouchen, Huan Li y 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 y 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 y 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 y 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 y 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 y 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. y 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 y 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 y 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 y 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 y 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 y 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 y 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 y 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 y 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 y 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 y 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 y Patrick Siarry. Optimization and Machine Learning: Optimization for Machine Learning and Machine Learning for Optimization. Wiley & Sons, Incorporated, John, 2022.

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

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

Chelouah, Rachid y 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 y Suvrit Sra. Optimization for Machine Learning. MIT Press, 2019.

Sra, Suvrit, Sebastian Nowozin y 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 y Suvrit Sra. Optimization for Machine Learning. MIT Press, 2011.

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

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

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

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

Satapathy, Suresh Chandra y 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 y 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 y 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.