Books on the topic 'Computational Learning Sciences'
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Ashwin, Ram, and Leake David B, eds. Goal-driven learning. Cambridge, Mass: MIT Press, 1995.
SEAL 2008 (2008 Melbourne, Vic.). Simulated evolution and learning: 7th international conference, SEAL 2008, Melbourne, Australia, December 7-10, 2008 : proceedings. Berlin: Springer, 2008.
A, Rosenbaum David, and Collyer Charles E, eds. Timing of behavior: Neural, psychological, and computational perspectives. Cambridge, Mass: MIT Press, 1998.
Baldi, Pierre. Bioinformatics: The machine learning approach. 2nd ed. Cambridge, Mass: MIT Press, 2001.
Judd, J. Stephen. Neural network design and the complexity of learning. Cambridge, Mass: MIT Press, 1990.
Kearns, Michael J. An introduction to computational learning theory. Cambridge, Mass: MIT Press, 1994.
ISICA, 2008 (2008 Wuhan China). Advances in computation and intelligence: Third international symposium, ISICA 2008 : Wuhan, China, December 19-21, 2008 : proceedings. Berlin: Springer, 2008.
ISICA 2007 (2007 Wuhan, China). Advances in computation and intelligence: Second international symposium, ISICA 2007, Wuhan, China, September 21-23, 2007 ; proceedings. Berlin: Springer, 2007.
ISICA 2008 (2008 Wuhan, China). Advances in computation and intelligence: Third international symposium, ISICA 2008 : Wuhan, China, December 19-21, 2008 : proceedings. Berlin: Springer, 2008.
ISICA 2008 (2008 Wuhan, China). Advances in computation and intelligence: Third international symposium, ISICA 2008 : Wuhan, China, December 19-21, 2008 : proceedings. Berlin: Springer, 2008.
ISICA 2009 (2009 Huangshi Shi, China). Advances in computation and intelligence: 4th International Symposium on Intelligence Computation and Applications, ISICA 2009, Huangshi, China, October 23-25, 2009 : proceedings. Berlin: Springer, 2009.
P, Roychowdhury Vwani, Siu Kai-Yeung 1966-, and Orlitsky Alon 1958-, eds. Theoretical advances in neural computation and learning. Boston: Kluwer Academic, 1994.
R, Gabriel Michael, and Moore John, eds. Learning and computational neuroscience: Foundations of adaptive networks. Cambridge, Mass: MIT Press, 1990.
Conference on Computational Learning Theory (14th 2001 Amsterdam, Netherlands). Computational learning theory: 14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, July 16-19, 2001 : proceedings. New York: Springer, 2001.
F, Luger George, ed. Computation and intelligence: Collected readings. Menlo Park, Calif: AAAI Press, 1995.
Roychowdhury, Vwani. Theoretical Advances in Neural Computation and Learning. Boston, MA: Springer US, 1994.
Kacprzyk, Janusz, Vasil Sgurev, and Mincho Hadjiski. Intelligent systems: From theory to practice. Berlin: Springer Verlag, 2010.
E, Hinton Geoffrey, and Sejnowski Terrence J, eds. Unsupervised learning: Foundations of neural computation. Cambridge, Mass: MIT Press, 1999.
National Research Council (U.S.). Committee for the Workshops on Computational Thinking. Report of a workshop of pedagogical aspects of computational thinking. Washington, D.C: National Academies Press, 2011.
Satapathy, Suresh Chandra, Vikrant Bhateja, and Joao Manuel R.S. Tavares. Information and Decision Sciences: Proceedings of the 6th International Conference on FICTA. Springer, 2018.
Satapathy, Suresh Chandra, Vikrant Bhateja, J. R. Mohanty, and Joao Manuel R.S. Tavares. Information and Decision Sciences: Proceedings of the 6th International Conference on FICTA. Springer, 2018.
Belgium) NATO Advanced Study Institute on Learning Theory and Practice (2002 : Louvain. Advances in Learning Theory: Methods, Models and Applications (Nato Science Series. Series III, Computer and Systems Sciences, V. 190). IOS Press, 2003.
Engel, Uwe, Anabel Quan-Haase, Sunny Xun Liu, and Lars E. Lyberg. Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods. Taylor & Francis Group, 2021.
Engel, Uwe, Anabel Quan-Haase, Sunny Xun Liu, and Lars E. Lyberg. Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods. Taylor & Francis Group, 2021.
Engel, Uwe, Anabel Quan-Haase, Sunny Xun Liu, and Lars E. Lyberg. Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods. Taylor & Francis Group, 2021.
Dzeroski, Saso, and Ljupco Todorovski. Computational Discovery of Scientific Knowledge: Introduction, Techniques, and Applications in Environmental and Life Sciences. Springer London, Limited, 2007.
Computational discovery of scientific knowledge: Introduction, techniques, and applications in environmental and life sciences. Berlin: Springer, 2007.
Busemeyer, Jerome R., Zheng Wang, James T. Townsend, and Ami Eidels, eds. The Oxford Handbook of Computational and Mathematical Psychology. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.001.0001.
Kirley, Michael, Zbigniew Michalewicz, Xiaodong Li, Mengjie Zhang, and Vic Ciesielski. Simulated Evolution and Learning: 7th International Conference, SEAL 2008, Melbourne, Australia, December 7-10, 2008, Proceedings. Springer London, Limited, 2008.
Wang, Tzai-Der, Xufa Wang, and Xiaodong Li. Simulated Evolution and Learning: 6th International Conference, SEAL 2006, Hefei, China, October 15-18, 2006, Proceedings. Springer London, Limited, 2006.
(Editor), Tzai-Der Wang, Xiaodong Li (Editor), Shu-Heng Chen (Editor), and Xufa Wang (Editor), eds. Simulated Evolution and Learning: 6th International Conference, SEAL 2006, Hefei, China, October 15-18, 2006, Proceedings (Lecture Notes in Computer Science). Springer, 2006.
(Editor), David A. Rosenbaum, and Charles E. Collyer (Editor), eds. Timing of Behavior: Neural, Psychological, and Computational Perspectives. The MIT Press, 1998.
Judd, J. Stephen. Neural Network Design and the Complexity of Learning. MIT Press, 2018.
Judd, J. Stephen, and Robert Hanna. Neural Network Design and the Complexity of Learning. MIT Press, 1990.
(Editor), Geoffrey Hinton, and Terrence J. Sejnowski (Editor), eds. Unsupervised Learning: Foundations of Neural Computation (Computational Neuroscience). The MIT Press, 1999.
(Editor), Ke Chen, and Lipo Wang (Editor), eds. Trends in Neural Computation (Studies in Computational Intelligence). Springer, 2006.
Gureckis, Todd M., and Bradley C. Love. Computational Reinforcement Learning. Edited by Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami Eidels. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.013.5.
Rolls, Edmund T. Brain Computations. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198871101.001.0001.
Anthony, M. H. G., and N. Biggs. Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science). Cambridge University Press, 1997.
Kane, Michael, Taylor Arnold, and Bryan W. Lewis. Computational Approach to Statistical Learning. Taylor & Francis Group, 2019.
Jain, Vishal. Handbook of Machine Learning for Computational Optimization. Taylor & Francis Group, 2021.
Kane, Michael, Taylor Arnold, and Bryan W. Lewis. Computational Approach to Statistical Learning. Taylor & Francis Group, 2019.
Kane, Michael, Taylor Arnold, and Bryan W. Lewis. Computational Approach to Statistical Learning. Taylor & Francis Group, 2019.
Kane, Michael, Taylor Arnold, and Bryan W. Lewis. Computational Approach to Statistical Learning. Taylor & Francis Group, 2019.
Kane, Michael, Taylor Arnold, and Bryan W. Lewis. Computational Approach to Statistical Learning. Taylor & Francis Group, 2019.
Kane, Michael, Taylor Arnold, and Bryan W. Lewis. Computational Approach to Statistical Learning. Taylor & Francis Group, 2020.
Yadav, Vikash, Parashu Ram Pal, and Chuan-Ming Liu, eds. Recent Developments in Artificial Intelligence and Communication Technologies. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97816810896761220101.
(Editor), David Helmbold, and Bob Williamson (Editor), eds. Computational Learning Theory: 14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning ... (Lecture Notes in Computer Science). Springer, 2001.
(Editor), Paul Fischer, and Hans U. Simon (Editor), eds. Computational Learning Theory: 4th European Conference, EuroCOLT'99 Nordkirchen, Germany, March 29-31, 1999 Proceedings (Lecture Notes in Computer Science). Springer, 1999.
Hennig, Philipp, Hans P. Kersting, and Michael A. Osborne. Probabilistic Numerics: Computation As Machine Learning. Cambridge University Press, 2022.