Books on the topic 'Adaptive machine learning'

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

Lopes, Noel, and Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-06938-8.

Bhanu, Bir. Genetic learning for adaptive image segmentation. Boston: Kluwer Academic Publishers, 1994.

He, Haibo. Self-adaptive systems for machine intelligence. Hoboken, N.J: Wiley-Interscience, 2011.

Whiteson, Shimon. Adaptive representations for reinforcement learning. Berlin: Springer Verlag, 2010.

Gori͡achkin, O. V. Metody slepoĭ obrabotki signalov i ikh prilozhenii͡a v sistemakh radiotekhniki i svi͡azi. Moskva: Radio i svi͡azʹ, 2003.

Wei, Chia-Hung. Machine learning techniques for adaptive multimedia retrieval: Technologies, applications, and perspectives. Hershey, PA: Information Science Reference, 2011.

1938-, Mendel Jerry M., ed. A Prelude to neural networks: Adaptive and learning systems. Englewood Cliffs, N.J: PTR Prentice Hall, 1994.

1975-, Butz Martin V., and International Conference on Simulation of Adaptive Behavior (9th : 2006 : Rome, Italy), eds. Anticipatory behavior in adaptive learning systems: From brains to individual and social behavior. Berlin: Springer, 2007.

Cichocki, Andrzej. Adaptive blind signal and image processing: Learning algorithms and applications. Chichester: J. Wiley, 2002.

Hayes-Roth, Barbara. An architecture for adaptive intelligent systems. Stanford, Calif: Stanford University, Dept. of Computer Science, 1993.

Príncipe, J. C. Kernel adaptive filtering: A comprehensive introduction. Hoboken, N.J: Wiley, 2010.

David, Hutchison. Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

Baldassarre, Gianluca. Intrinsically Motivated Learning in Natural and Artificial Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

International, Conference on Artificial Neural Networks and Genetic Algorithms (2007 Warsaw Poland). Adaptive and natural computing algorithms: 8th international conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007 : proceedings. Berlin: Springer, 2007.

Rieser, Verena. Reinforcement Learning for Adaptive Dialogue Systems: A Data-driven Methodology for Dialogue Management and Natural Language Generation. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

Learning from data: Concepts, theory, and methods. 2nd ed. Hoboken, NJ: Wiley-Interscience, 2008.

Filip, Mulier, ed. Learning from data: Concepts, theory, and methods. New York: Wiley, 1998.

1931-, Haykin Simon S., ed. Neural networks and learning machines. 3rd ed. Upper Saddle River, N.J: Prentice Hall, 2008.

Kolehmainen, Mikko. Adaptive and Natural Computing Algorithms: 9th International Conference, ICANNGA 2009, Kuopio, Finland, April 23-25, 2009, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

Mars, P. Learning algorithms: Theory and applications in signal processing, control, and communications. Boca Raton: CRC Press, 1996.

Rastrigin, Leonard Andreevich. Adaptivnoe obuchenie s modelʹi͡u︡ obuchaemogo. Riga: "Zinatne", 1988.

Bierwirth, Christian. Adaptive Search and the Management of Logistic Systems: Base Models for Learning Agents. Boston, MA: Springer US, 2000.

Brabazon, Anthony. Natural Computing in Computational Finance. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

International, Joint Conference on Artificial Intelligence (14th 1995 Montréal Québec). Adaption and learning in multi-agent systems: IJCAI '95 workshop, Montréal, Canada, August 21, 1995, proceedings. Berlin: Springer, 1996.

(Editor), Olivier Chapelle, Bernhard Schölkopf (Editor), and Alexander Zien (Editor), eds. Semi-Supervised Learning (Adaptive Computation and Machine Learning). The MIT Press, 2006.

Lopes, Noel, and Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - a Practical Approach. Springer, 2014.

Lopes, Noel, and Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Springer, 2016.

Lopes, Noel, and Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Springer, 2014.

Lopes, Noel, and Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Springer, 2014.

Principe, Jos, Simon Haykin, and Weifeng Liu. Kernel Adaptive Filtering. Wiley & Sons, Incorporated, John, 2010.

(Editor), Lise Getoor, and Ben Taskar (Editor), eds. Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning). The MIT Press, 2007.

Blokdyk, Gerardus. Adaptive Machine Learning a Complete Guide - 2020 Edition. Emereo Pty Limited, 2020.

Shen, Jun, Geng Sun, and Jiayin Lin. Adaptive Micro Learning - Using Fragmented Time to Learn. World Scientific Publishing Co Pte Ltd, 2020.

Herbrich, Ralf. Learning Kernel Classifiers: Theory and Algorithms (Adaptive Computation and Machine Learning). The MIT Press, 2001.

(Editor), Kerstin Dautenhahn, and Chrystopher L. Nehaniv (Editor), eds. Imitation in Animals and Artifacts (Complex Adaptive Systems). The MIT Press, 2002.

Amari, Shun-ichi, and Andrzej Cichocki. Adaptive Blind Signal and Image Processing. Wiley, 2002.

Principles of Data Mining (Adaptive Computation and Machine Learning). The MIT Press, 2001.

Schlkopf, Bernhard, and Alexander J. Smola. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning). The MIT Press, 2001.

Whiteson, Shimon. Adaptive Representations for Reinforcement Learning. Springer Berlin / Heidelberg, 2014.

Haykin, Simon, José C. Principe, and Weifeng Liu. Kernel Adaptive Filtering: A Comprehensive Introduction. Wiley & Sons, Incorporated, John, 2010.

Haykin, Simon, José C. Principe, and Weifeng Liu. Kernel Adaptive Filtering: A Comprehensive Introduction. Wiley & Sons, Incorporated, John, 2011.

Haykin, Simon, José C. Principe, and Weifeng Liu. Kernel Adaptive Filtering: A Comprehensive Introduction. Wiley & Sons, Incorporated, John, 2011.

Haykin, Simon, José C. Principe, and Weifeng Liu. Kernel Adaptive Filtering: A Comprehensive Introduction. Wiley & Sons, Incorporated, John, 2010.

Chatterjee, Chanchal, and Vwani Roy Chowdhury. Adaptive Machine Learning Algorithms with Python: Solve Data Analytics and Machine Learning Problems on Edge Devices. Apress L. P., 2022.

Wang, Ding, and Chaoxu Mu. Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems. Springer, 2019.

Wang, Ding, and Chaoxu Mu. Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems. Springer, 2018.

Doursat, René, Nicolas Bredeche, and Taras Kowaliw. Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. Springer, 2016.

Doursat, René, Nicolas Bredeche, and Taras Kowaliw. Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. Springer, 2014.

Doursat, René, Nicolas Bredeche, and Taras Kowaliw. Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. Springer London, Limited, 2014.