Luc's Library

Neural networks books

Last update: Mon Apr 15 11:09:00 EDT 2013

	Luc's library has now opened its web doors to all McGill University students. The library is in fact my office (room 300N, McConnell Engineering Building), and the books are a subset of my private collection. Any McGill student may borrow any book at any time!

Laurence Abbott Terrence J. Sejnowski (eds)	Neural Codes and Distributed Representations Foundations of Neural Computation MIT Press, Cambridge, MA, 1999.
J.A. Anderson E. Rosenfeld (eds)	Neurocomputing: Foundations of Research MIT Press, Cambrige, 1988.
M. Anthony P.L. Bartlett	Neural Network Learning: Theoretical Foundations Cambridge University Press, Cambridge, 1999.
M. Anthony	Discrete Mathematics of Neural Networks Selected Topics SIAM, Philadelphia, 2001.
M. A. Arbib (ed.)	The Handbook of Brain Theory and Neural Networks MIT Press, Cambridge, MA, 1998.
Christopher M. Bishop	Pattern Recognition and Machine Learning Springer-Verlag, New York, 2006.
C.M. Bishop	Neural Networks for Pattern Recognition Clarendon Press, Oxford, 1995.
C.M. Bishop	Neural Networks for Pattern Recognition Clarendon Press, Oxford, 1995.
G.A. Carpenter S. Grossberg (eds)	Pattern Recognition by self-Organizing Neural Networks MIT Press, Cambrige, 1988.
A. Cichocki R. Unbehauen	Neural Networks for Optimization and Signal Processing John wiley, Chichester, 1993.
Eduardo Bayro Corrochano	Handbook of Geometric Computing Springer-Verlag, Berlin, 2005.
N. Cristianini J. Shawe-Taylor	An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods Cambridge University Press, Cambridge, UK, 2000.
Nelio Cristianini John Shawe-Taylor	An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods Cambridge University Press, Cambridge, UK, 2000.
L. Devroye L. Györfi G. Lugosi	A Probabilistic Theory of Pattern Recognition Springer-Verlag, New York, 1996.
Thomas G. Dietterich Suzanna Becker Zoubin Ghahramani (eds)	Neural Information Processing Systems 14 Volume 2 MIT Press, Cambridge, MA, 2002.
Thomas G. Dietterich Suzanna Becker Zoubin Ghahramani (eds)	Neural Information Processing Systems 14 Volume 1 MIT Press, Cambridge, MA, 2002.
D. Graupe	Principles of Artificial Neural Networks World Scientific Publishing Co., Singapore, 1997.
Ralf Herbrich	Learning Kernel Classifiers Theory and Algorithms MIT Press, Cambridge, MA, 2002.
J. Hertz A. Krogh R.G. Palmer	Introduction to the Theory of Neural Computation Addison-Wesley, Redwood City, CA, 1991.
D. Husmeier	Neural Networks for Conditional Probability Estimation Springer-Verlag, London, 1999.
Alan Hutchinson	Algorithmic Learning Clarendon Press, Oxford, 1994.
Michael I. Jordan (ed)	Learning in Graphical Models MIT Press, 1999.
P.U. Lima G.N. Saridis	Design of Intelligent Control Systems based on Hierarchical Stochastic Automata World Scientific Publishing Co., Singapore, 1996.
M. Mozer M. Jordan T. Petsche (eds.)	Neural Information Processing Systems MIT Press, Cambridge, MA, 1997.
R.M. Neal	Bayesian Learning for Neural Networks Springer-Verlag, New York, 1996.
R.M. Neal	Bayesian Learning for Neural Networks Springer-Verlag, New York, 1996.
Sarunas Raudys	Statistical and Neural Classifiers Springer-Verlag, London, 2001.
A.F. Rocha	Neural Nets Springer-Verlag, Berlin, 1992.
W.F. Schmidt	Neural Pattern Classifying Systems (Ph.D. dissertation) Technical University of Delft, Delft, The Netherlands, 1994.
B. Schölkopf C.J.C. Burges A.J. Smola (eds)	Advances in Kernel Methods Support Vector Learning MIT Press, Cambridge, MA, 1999.
Bernhard Schölkopf Alexander J. Smola	Learning with Kernels MIT Press, Cambridge, MA, 2002.
J. Schürmann	Pattern Classification: A Unified View of Statistical and Neural Approaches John Wiley, New York, 1996.
I.K. Sethi A.K. Jain (eds)	Artificial Neural Networks and Statistical Pattern Recognition North Holland, Amsterdam, 1991.
J. Shawe-Taylor N. Cristianini	Kernel Methods for Pattern Analysis Cambridge University Press, Cambridge, UK, 2004.
D.M. Skapura	Building Neural Networks ACM Press, New York, 1996.
A.J. Smola P.L. Bartlett B. Schölkopf D. Schuurmans(eds)	Advances in Large Margin Classifiers MIT Press, Cambridge, MA, 2000.
J.A.K. Suykens J.P.L. Vandewalle B.L.R. De Moor	Artificial Neural Networks for Modelling and Control of Non-Linear Systems Kluwer Academic Publishers, Boston, 1996.
Johan Suykens Gábor Horváth Sankar Bau Charles Micchelli Joos Vandewalle (eds)	Advances in Learning Theory: Methods, Models and Applications IOS Press, Amsterdam, 2003.
S. Thiria Y. Lechevallier O. Gascuel S. Canu	Statistique et méthodes neuronales Dunod, Paris, 1997.
V. Torre J. Nicholls	Neural Circuits and Networks Springer-Verlag, New York, 1998.
A.J.F. van Rooij L.C. Jain R.P. Johnson	Neural Network Training using Genetic Algorithms World Scientific Publishing Co., Singapore, 1996.
Vladimir Vapnik	Statistical Learning Theory John Wiley, New York, 1998.
V.N. Vapnik	The Nature of Statistical Learning Theory Springer-Verlag, New York, 1995.
V.N. Vapnik	The Nature of Statistical Learning Theory (2nd ed) Springer-Verlag, New York, 2000.
P. Whittle	Neural Nets and Chaotic Carriers John Wiley, Chichester, 1998.
Kwok-Yee Michael Wong Irwin King Dit-Yan Yeung (eds)	Theoretical Aspects of Neural Computation Springer-Verlag, Singapore, 1998.

Contact

Luc Devroye
School of Computer Science
McGill University
Montreal, Canada H3A 2K6
lucdevroye@gmail.com
http://cg.scs.carleton.ca/~luc