Luc's Library

Pattern recognition books

Last update: Mon Apr 15 11:09:02 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!

M. Anthony N. Biggs	Computational Learning Theory Cambridge University Press, Cambridge, 1992.
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.
Jean-Yves Audibert	PAC-Bayesian Statistical Learning Theory Paris, France, 2004.
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.
L. Breiman J. H. Friedman R. A. Olshen C. J. Stone	Classification and Regression Trees Wadsworth International, Belmont, CA., 1984.
G.A. Carpenter S. Grossberg (eds)	Pattern Recognition by self-Organizing Neural Networks MIT Press, Cambrige, 1988.
Nicolo Cesa-Bianchi Gabor Lugosi	Prediction, Learning, and Games Cambridge University Press, New York, 2006.
D. Coomans I. Broeckaert	Potential Pattern Recognition in Chemical and Medical Decision Making John Wiley, New York, 1986.
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.
B.V. Dasarathy	Nearest Neighbor Pattern Classification Techniques IEEE Computer Society Press, Los Alamitos, CA, 1991.
Anirban DasGupta	Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics Springer, New York, 2011.
Isabelle De Macq	Hyperrectangular Space Partitioning Trees Louvain, Belgium, 2004.
P.A. Devijver J. Kittler	Pattern Recognition: A Statistical Approach Prentice-Hall, London, 1982.
Pierre A. Devijver Josef Kittler (eds)	Pattern Recognition Theory and Applications Springer-Verlag, Berlin, 1987.
L. Devroye L. Györfi G. Lugosi	A Probabilistic Theory of Pattern Recognition Springer-Verlag, New York, 1996.
A.C. Downton S. Impedovo (eds)	Progress in Handwriting Recognition World Scientific Publishing Co., Singapore, 1997.
M. Dror P. L'Ecuyer F. Szidarovszky (eds)	Modeling Uncertainty Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002.
R. O. Duda P. E. Hart	Pattern Classification and Scene Analysis John Wiley, New York, 1973.
R. O. Duda P. E. Hart D. G. Stork	Pattern Classification (2nd ed.) John Wiley, New York, 2001.
R.P.W. Duin	On the accuracy of statistical pattern recognizers Dutch Efficiency Bureau, Pijnacker, The Netherlands, 1978.
Brendan J. Frey	Graphical Models for Machine Learning and Digital Communication MIT Press, Cambridge, MA, 1998.
K.S. Fu	Syntactic Methods in Pattern Recognition Academic Press, New York, 1974.
K.S. Fu	Syntactic Pattern Recognition and Applications Academic Press, New York, 1982.
L. Györfi (ed.)	Principles of Nonparametric Learning Springer-Verlag, Wien, 2002.
L. Györfi M. Kohler A. Krzyzak H. Walk	A Distribution-Free Theory of Conparametric Regression Springer-Verlag, New York, 2002.
T. Hastie R. Tibshirani J. Friedman	The Elements of Statistical Learning Springer-Verlag, New York, 2001.
Ralf Herbrich	Learning Kernel Classifiers Theory and Algorithms MIT Press, Cambridge, MA, 2002.
IEEE	Proceedings of the Third International Joint Conference on Pattern Recognition IEEE Computer Society, Piscataway, NJ, 1976.
IEEE	Proceedings of the 1973 IEEE Conference on Decision and Control IEEE, New York, 1993.
A.K. Jain R.C. Dubes	Algorithms for Clustering Data Prentice Hall, Englewood Cliffs, NJ, 1988.
F. Jelinek	Statistical Methods for Speech Recognition MIT Press, Cambridge, MA, 1998.
Ludmila I. Kuncheva	Combining Pattern Classifiers Methods and Algorithms John Wiley, New York, 2004.
G. Lorette	Proceedings of the 1996 French-Korean Workshop on Man-Machine Handwritten Communication CNRS, Paris, 1996.
Gabor Lugosi Hans Ulrich Simon (eds)	Learning Theory 19th Annual Conference on Learning Theory COLT 2006 Springer-Verlag, Berlin, 2006.
David J. Marchette	Random Graphs for Statistical Pattern Recognition John Wiley, Hoboken, NJ, 2003.
G.J. McLachlan	Discriminant Analysis and Statistical Pattern Recognition John Wiley, New York, 1992.
M. Mozer M. Jordan T. Petsche (eds.)	Neural Information Processing Systems MIT Press, Cambridge, MA, 1997.
D.W. Murray B.F. Buxton	Experiments in the Machine Interpretation of Visual Motion MIT Press, Cambridge, MA, 1990.
S.K. Pal P.P. Wang (eds)	Genetic Algorithms for Pattern Recognition CRC Press, Boca Raton, FL, 1996.
R. Plamondon C.Y. Suen M.L. Simmer (eds)	Computer Recognition and Human Production of Handwriting World Scientific, Singapore, 1989.
Sarunas Raudys	Statistical and Neural Classifiers Springer-Verlag, London, 2001.
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.
A.J. Smola P.L. Bartlett B. Schölkopf D. Schuurmans(eds)	Advances in Large Margin Classifiers MIT Press, Cambridge, MA, 2000.
Johan Suykens Gábor Horváth Sankar Bau Charles Micchelli Joos Vandewalle (eds)	Advances in Learning Theory: Methods, Models and Applications IOS Press, Amsterdam, 2003.
J.T. Tou R.C. Gonzalez	Pattern Recognition Principles Addison-Wesley, Reading, MA, 1974.
V. N. Vapnik	Estimation of Dependences Based on Empirical Data Springer-Verlag, New York, 1982.
Vladimir Vapnik	Statistical Learning Theory John Wiley, New York, 1998.
Vladimir Vapnik	Estimation of Dependences Based on Empirical Data Springer Science and Business Media, New York, 2006.
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.
D. Wolpert (ed)	The Mathematics of Generalization: Proceedings of the SFI/CNLS Workshop on Formal Approaches to Supervised Learning Addison-Wesley, Reading, MA, 1994.

Contact

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