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 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!
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M. Anthony
N. Biggs
| Computational Learning Theory [Google]
Cambridge University Press,
Cambridge,
1992. |
M. Anthony
P.L. Bartlett
| Neural Network Learning: Theoretical Foundations [Google]
Cambridge University Press,
Cambridge,
1999. |
M. Anthony
| Discrete Mathematics of Neural Networks Selected Topics [Google]
SIAM,
Philadelphia,
2001. |
M. A. Arbib (ed.)
| The Handbook of Brain Theory and Neural Networks [Google]
MIT Press,
Cambridge, MA,
1998. |
Jean-Yves Audibert
| PAC-Bayesian Statistical Learning Theory [Google]
Paris, France,
2004. |
Peter Auer
Alexander Clark
Thomas Zeugmann
Sandra Zilles (eds)
| Algorithmic Learning Theory [Google]
Springer,
Cham,
2014. |
J.D. Becker
I. Eisele
F.W. Mündemann
| Parallelism, Learning, Evolution. WOPPLOT 89 [Google]
Springer-Verlag,
Berlin,
1991. |
Michael W. Berry
Murray Browne (eds)
| Lecture Notes in Data Mining [Google]
Singapore,
2006. |
Christopher M. Bishop
| Pattern Recognition and Machine Learning [Google]
Springer-Verlag,
New York,
2006. |
Léon Bottou
Olivier Chapelle
Dennis DeCoste
Jason Weston
| Large-Scale Kernel Machines [Google]
MIT Press,
Cambridge, MA,
2007. |
Nicolo Cesa-Bianchi
Gabor Lugosi
| Prediction, Learning, and Games [Google]
Cambridge University Press,
New York,
2006. |
Eduardo Bayro Corrochano
| Handbook of Geometric Computing [Google]
Springer-Verlag,
Berlin,
2005. |
N. Cristianini
J. Shawe-Taylor
| An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods [Google]
Cambridge University Press,
Cambridge, UK,
2000. |
Nelio Cristianini
John Shawe-Taylor
| An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods [Google]
Cambridge University Press,
Cambridge, UK,
2000. |
Anirban DasGupta
| Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics [Google]
Springer,
New York,
2011. |
Thomas G. Dietterich
Suzanna Becker
Zoubin Ghahramani (eds)
| Neural Information Processing Systems 14 Volume 2 [Google]
MIT Press,
Cambridge, MA,
2002. |
Thomas G. Dietterich
Suzanna Becker
Zoubin Ghahramani (eds)
| Neural Information Processing Systems 14 Volume 1 [Google]
MIT Press,
Cambridge, MA,
2002. |
M. Dror
P. L'Ecuyer
F. Szidarovszky (eds)
| Modeling Uncertainty [Google]
Kluwer Academic Publishers,
Dordrecht, The Netherlands,
2002. |
Saso Dzeroski
Pance Panov
Dragi Kocev
Ljupco Todorovski (eds)
| Discovery Science [Google]
Springer,
Cham,
2014. |
D. Fisher
H.-J. Lenz (eds)
| Learning from Data: Artificial Intelligence and Statistics V [Google]
Springer-Verlag,
New York,
1996. |
Brendan J. Frey
| Graphical Models for Machine Learning and Digital Communication [Google]
MIT Press,
Cambridge, MA,
1998. |
M. Fulk
J. Case (eds)
| COLT'90: Proceedings of the Third Annual Workshop on Computational Learning Theory [Google]
Morgan Kaufmann,
San Mateo, CA,
1990. |
D.E. Goldberg
| Genetic Algorithms in Search Optimization and Machine Learning [Google]
Addison-Wesley,
Reading, MA,
1989. |
Ian Goodfellow
Yoshua Bengio
Aaron Courville
| Deep Learning [Google]
MIT Press,
Cambridge, MA,
2016. |
L. Györfi (ed.)
| Principles of Nonparametric Learning [Google]
Springer-Verlag,
Wien,
2002. |
Laszlio Gyorfi
Gyorgy Ottucsak
Harro Walk
| Machine Learning for Financial Engineering [Google]
Imperial College Press,
London,
2012. |
T. Hastie
R. Tibshirani
J. Friedman
| The Elements of Statistical Learning [Google]
Springer-Verlag,
New York,
2001. |
Trevor Hastie
Robert Tibshirani
Martin Wainwright
| Statistical Learning with Sparsity The Lasso and Generalizations [Google]
CRC Press,
Boca Raton, FL,
2015. |
D. Haussler (ed)
| COLT'92: Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory [Google]
ACM,
New York,
1992. |
Ralf Herbrich
| Learning Kernel Classifiers Theory and Algorithms [Google]
MIT Press,
Cambridge, MA,
2002. |
U. Herkenrath
D. Kalin
W. Vogel (eds)
| Mathematical Learning Models---Theory and Algorithms [Google]
Springer-Verlag,
New York,
1983. |
Alan Hutchinson
| Algorithmic Learning [Google]
Clarendon Press,
Oxford,
1994. |
M. Iosifescu
R. Theodorescu
| Random Processes and Learning [Google]
Springer-Verlag,
New York,
1969. |
F. Jelinek
| Statistical Methods for Speech Recognition [Google]
MIT Press,
Cambridge, MA,
1998. |
Michael I. Jordan (ed)
| Learning in Graphical Models [Google]
MIT Press,
1999. |
M.J. Kearns
| The Computational Complexity of Machine Learning [Google]
MIT Press,
Cambridge, MA,
1990. |
M.J. Kearns
U. Vazirani
| An Introduction to Computational Learning Theory [Google]
MIT Press,
Cambridge, MA,
1994. |
Ludmila I. Kuncheva
| Combining Pattern Classifiers Methods and Algorithms [Google]
John Wiley,
New York,
2004. |
J. Laird (ed)
| Proceedings of the Fifth International Conference on Machine Learning [Google]
Morgan Kaufmann,
San Mateo, CA,
1988. |
Tor Lattimore
Csaba Szepesvari
| Bandit Algorithms [Google]
Cambridge University Press,
Cambridge, UK,
2020. |
P.U. Lima
G.N. Saridis
| Design of Intelligent Control Systems based on Hierarchical Stochastic Automata [Google]
World Scientific Publishing Co.,
Singapore,
1996. |
Gabor Lugosi
Hans Ulrich Simon (eds)
| Learning Theory 19th Annual Conference on Learning Theory COLT 2006 [Google]
Springer-Verlag,
Berlin,
2006. |
Mehryar Mohri
Afshin Rostamizadeh
Ameet Talwalkar
| Foundations of Machine Learning [Google]
MIT Press,
Cambridge, MA,
2012. |
M. Mozer
M. Jordan
T. Petsche (eds.)
| Neural Information Processing Systems [Google]
MIT Press,
Cambridge, MA,
1997. |
B.K. Natarajan
| Machine Learning: A Theoretical Approach [Google]
Morgan Kaufmann,
San Mateo,
1991. |
R.M. Neal
| Bayesian Learning for Neural Networks [Google]
Springer-Verlag,
New York,
1996. |
R.M. Neal
| Bayesian Learning for Neural Networks [Google]
Springer-Verlag,
New York,
1996. |
M.F. Norman
| Markov Processes and Learning Models [Google]
Academic Press,
New York,
1972. |
L. Pitt (ed)
| COLT'93: Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory [Google]
ACM,
New York,
1993. |
B. Porter
R.J. Mooney (eds)
| Proceedings of the Seventh International Conference on Machine Learning [Google]
Morgan Kaufmann,
San Mateo, CA,
1990. |
J.R. Quinlan
| C4.5: Programs for Machine Learning [Google]
Morgan Kaufmann,
San Mateo,
1993. |
Robert E. Schapire
Yoav Freund
| Boosting Fondations and Algorithms [Google]
MIT Press,
Cambridge, MA,
2012. |
Robert E. Schapire
Yoav Freund
| Boosting Fondations and Algorithms (Paperback Edition) [Google]
MIT Press,
Cambridge, MA,
2014. |
B. Schölkopf
C.J.C. Burges
A.J. Smola (eds)
| Advances in Kernel Methods Support Vector Learning [Google]
MIT Press,
Cambridge, MA,
1999. |
Bernhard Schölkopf
Alexander J. Smola
| Learning with Kernels [Google]
MIT Press,
Cambridge, MA,
2002. |
E.M. Segre (ed)
| Proceedings of the Sixth International Conference on Machine Learning [Google]
Morgan Kaufmann,
San Mateo, CA,
1989. |
J. Setubal
J. Meidanis
| Introduction to Computational Molecular Biology [Google]
PWS Publishing Company,
Boston,
1997. |
J. Shawe-Taylor
N. Cristianini
| Kernel Methods for Pattern Analysis [Google]
Cambridge University Press,
Cambridge, UK,
2004. |
A.J. Smola
P.L. Bartlett
B. Schölkopf
D. Schuurmans(eds)
| Advances in Large Margin Classifiers [Google]
MIT Press,
Cambridge, MA,
2000. |
Johan Suykens
Gábor Horváth
Sankar Bau
Charles Micchelli
Joos Vandewalle (eds)
| Advances in Learning Theory: Methods, Models and Applications [Google]
IOS Press,
Amsterdam,
2003. |
Ya.Z. Tsypkin
| Adaptation and Learning in Automatic Systems [Google]
Academic Press,
New York,
1971. |
Ya.Z. Tsypkin
| Foundations of the Theory of Learning Systems [Google]
Academic Press,
New York,
1973. |
L. Valiant
M.K. Warmuth (eds)
| COLT'91: Proceedings of the Fourth Annual Workshop on Computational Learning Theory [Google]
Morgan Kaufmann,
San Mateo, CA,
1991. |
Leslie Valiant
| Probably Approximately Correct [Google]
Basic Books,
New York,
2013. |
Leslie Valiant
| Probably Approximately Correct [Google]
Basic Books,
New York,
2013. |
Vladimir Vapnik
| Statistical Learning Theory [Google]
John Wiley,
New York,
1998. |
V.N. Vapnik
| The Nature of Statistical Learning Theory [Google]
Springer-Verlag,
New York,
1995. |
V.N. Vapnik
| The Nature of Statistical Learning Theory (2nd ed) [Google]
Springer-Verlag,
New York,
2000. |
Martin J. Wainwright
Michael I. Jordan
| Graphical Models, Exponential Families, and Variational Inference [Google]
NOW,
Boston,
2008. |
Michael S. Waterman
| Introduction to Computational Biology [Google]
Chapman and Hall,
London,
1995. |
S. Weiss
C. Kulikowski
| Computer Systems that Learn [Google]
Morgan Kaufmann Publishers,
San Mateo, CA,
1990. |
D. Wolpert (ed)
| The Mathematics of Generalization: Proceedings of the SFI/CNLS Workshop on Formal Approaches to Supervised Learning [Google]
Addison-Wesley,
Reading, MA,
1994. |
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