- Martin Anthony
and Joel Ratsaby, Quantifying accuracy of learning via sample width.
Proceedings of the 2013 IEEE Symposium on Foundations of Computational
Intelligence, April 2013.
- Martin Anthony and
Michele Harvey,
Further Linear Algebra, University
of London 2012.
- Martin
Anthony and Michele Harvey, Algebra,
University of London 2011.
- Martin
Anthony, The Beauty of Maths, LSE
Connect,
Summer 2011. (An expository article for non-mathematicians.)
- Martin Anthony. On constructing threshold networks for pattern
classification. In Constructive
Neural
Networks (eds. Leonardo Franco, David Elizondo, Jose
Jerez), Springer Studies in Computational Intelligence Vol. 258,
Springer, 2009.
- Martin
Anthony, Advanced
Mathematical
Analysis, University
of
London Press 2007.
- Leonardo
Franco and Martin Anthony. The influence of oppositely classified
examples on the generalization complexity of Boolean functions. IEEE
Transactions on Neural Networks, 17 (3), 2006, 578-590.
- Leonardo
Franco, Jose Luis Subirats, Martin Anthony and Jose Jerez. A new
constructive approach for creating all linearly separable
(threshold) functions. Proceedings
of
the 2006 IEEE International Joint Conference on Neural Networks.
- Martin
Anthony, Abstract
Mathematics,
University
of
London Press 2006.
- Martin
Anthony and Michele Harvey, Advanced
Linear
Algebra, University
of
London Press 2006.
- Martin Anthony, On learning a function of perceptrons. Proceedings
of the 2004 IEEE International Joint Conference on Neural Networks,
2004.
- Leonardo
Franco and Martin Anthony, On a generalization complexity measure
for Boolean functions. Proceedings
of the 2004 IEEE International Joint Conference on Neural Networks,
2004.
- Martin Anthony,
Generalization Error Bounds for Threshold Decision Lists. Journal
of Machine Learning Research 5 (2004):
189-217, February 2004 (pdf
| ps)
- Martin Anthony, Data
classification by multithreshold functions. Workshop on Discrete
Mathematics and Data Mining, 3rd SIAM Conference on Data Mining, San
Francisco, May 2003.
- Martin Anthony, Accuracy of
classification by iterative linear thresholding. Workshop on
Discrete Mathematics and Data Mining, 3rd SIAM Conference on Data
Mining, San Francisco, May 2003.
- Martin Anthony and
Norman Biggs, PAC learning and artificial neural networks. In
The Handbook of Brain Theory and Neural Networks, Second Edition,
(ed. Michael A. Arbib), Bradford Books/MIT Press, November 2002.
- Martin Anthony, Uniform
Glivenko-Cantelli
Theorems
and Concentration of Measure in the Mathematical Modelling of
Learning. CDAM Research Report LSE-CDAM-2002-07, May 2002. (pdf)
- Martin Anthony and
Norman Biggs, Matemática Para la
Economía y las Finanzas, Cambridge University Press
(Spanish translation of Mathematics
for
Economics and Finance) (January 2002. ISBN:
848323248)
- Martin Anthony,
Mathematical Modelling of Generalization. In M. Marinaro, R.
Tagliaferri (eds.), Neural Nets: 13th ItalianWorkshop on Neural
Nets, WIRN VIETRI 2002 Vietri sul Mare, Italy, May 30 – June 1,
2002. Springer LNCS 2486, 2002. (pdf)
- Martin Anthony, The
Classification of Undergraduate Degrees in the United Kingdom: An
Analysis of Problems with the Honours System. MA Research
Report, Institute of Education, 2002.
- Martin Anthony, Mathematics
1, University of London Press 2002.
- Martin Anthony, Mathematics
2, University of London Press, 2002.
- Martin
Anthony, Discrete Mathematics of
Neural Networks: Selected Topics. SIAM
Monographs on Discrete Mathematics and Applications, Number 8, SIAM
(Society for Industrial and Applied Mathematics), Philadelphia, USA,
2001. (ISBN 0 89871 480 X)
- Martin Anthony and Peter
Bartlett, Function learning from interpolation. Combinatorics,
Probability and Computing, 2000 (pdf
| ps)
- Martin Anthony and Peter
Bartlett, Neural Network
Learning: Theoretical Foundations, Cambridge
University
Press, Cambridge, UK, 1999. (ISBN
0 521 57353 X.)
- Martin Anthony,
Accuracy of techniques for the logical analysis of data. Discrete
Applied Mathematics 96, 247--257, 1999. (pdf
| ps) (Also, RUTCOR Research Report RRR 23-96,
RUTCOR, Rutgers Center for Operations Research.)
- Martin Anthony. Further
Mathematics
for
Economists (a subject guide for External Programmes) , 1999,
Univ. London.
- Martin Anthony and Sean
B. Holden, Cross-validation for binary classification by real-valued
functions. In Proceedings of the 1998 Annual Conference on
Computational Learning Theory.(COLT’98), Madison, Wisconsin,
1998. ACM Press. Full version: (pdf | ps)
- Martin Anthony, R. Hewins
and C. Phillips,
Quantitative Methods, (a subject guide for External Programmes), 1998,
Univ.
London; ISBN: 0718715209.
- John Shawe-Taylor,
Peter L. Bartlett, Robert C. Williamson and Martin Anthony,
Structural risk minimization over data-dependent hierarchies. IEEE
Transactions on Information Theory. 44(5), 1926--1940, 1998. (ps)
- Martin Anthony,
Probabilistic `generalization' of functions and dimension-based
uniform convergence results. Statistics and Computing, 8(1),
5--14, 1998. (pdf | ps)
- Martin Anthony,
Artificial neural networks. In Graph Connections (ed.
Lowell Beineke and Robin Wilson). Oxford University Press, 1997. ((pdf
| ps), without figures)
- Martin Anthony,
Probabilistic analysis of learning in artificial neural networks:
the PAC model and its variants. Neural Computing Surveys, 1,
1--47, 1997. (html
| pdf
| ps.gz)
- Martin Anthony. Mathematics
for Economists (a subject guide for External Programmes), June
1997, Univ. London; ISBN: 07187144311997.
- Martin Anthony and John
Shawe-Taylor, A sufficient condition for polynomial
distribution-dependent learnability. Discrete Applied
Mathematics, 77(1), 1--12, 1997. (pdf
| ps)
- John Shawe-Taylor,
Peter L. Bartlett, Robert C. Williamson and Martin Anthony, A
framework for structural risk minimisation. In Proceedings of
the 1996 Annual Conference on Computational Learning Theory
(COLT'96), 68--76. ACM Press, 1996.
- Martin Anthony, Peter
Bartlett, Yuval Ishai and John Shawe-Taylor, Valid generalisation
from approximate interpolation. Combinatorics, Probability and
Computing, Volume 5, 191--214 (1996). (pdf
| ps)
- Martin Anthony and Norman
Biggs. Mathematics for Economics
and Finance: Methods and Modelling.
Cambridge University Press, Cambridge, UK, 1996. (h/b
ISBN 0 521 55913 8, p/b ISBN 0 521 55113 7).
Reprinted several
times, with Japanese and Chinese versions.
- Martin Anthony, Threshold
functions,
decision lists, and the representation of Boolean functions. Neurocolt
Technical
Report NC-TR-96-028. (ps.gz)
- Martin Anthony, Mathematics
(for
Diploma
in
Economics), (a subject guide for External Programmes), May
1996, Univ. London; ISBN: 0718713508.
- Martin Anthony and Norman
Biggs, A computational learning theory view of economic forecasting
with neural nets. In Neural Networks in the Capital Markets,
(ed. A.N. Refenes), Wiley, 1995.
- Martin Anthony,
Interpolation and learning in artificial neural networks. In Proceedings
of the 1995 IEEE International Conference on Neural Networks,
Perth, Western Australia. IEEE Press.
- Martin Anthony, Graham
Brightwell and John Shawe-Taylor, On specifying Boolean functions by
labelled examples. Discrete Applied Mathematics, 61 (1995):
1--25. (pdf | ps)
- Martin Anthony,
Classification by polynomial surfaces. Discrete Applied
Mathematics, 61 (1995): 91--103.(pdf
| ps)
- Martin Anthony and
Peter Bartlett, Function learning from interpolation. In Proceedings
EuroCOLT'95,
Springer-Verlag, (1995): 211--221.
- Martin Anthony, Graham
Brightwell and Colin Cooper, On the Vapnik-Chervonenkis dimension of
a random graph. Discrete Mathematics 138 (1995): 43--56. (pdf
| ps)
- Martin Anthony and
Norman Biggs, Pac learning and artificial neural networks. In The
Handbook of Brain Theory and Neural Networks (ed. Michael A
Arbib) Bradford Books/MIT Press, 1995. (pdf
| ps)
- Martin Anthony and John
Shawe-Taylor, Valid generalisation of functions from close
approximations on a sample. In Computational Learning Theory:
EuroCOLT'93, 95--108, Oxford University Press 1994.
- Martin Anthony, Probabilistic
learning
theory, with emphasis on sample complexity. Report 94-002,
Sonderforschungsbereich 343, Diskrete Structuren in der Mathematik,
Universitat Bielefeld, 1994.
- Martin Anthony and Sean
B. Holden, Quantifying generalisation in linearly weighted neural
networks. Complex Systems 8, (1994), 91--114. (pdf
| ps)
- Martin Anthony, On the
mean chromatic number, Discrete Mathematics, Volume 125
(1994): 11--14.
- John Shawe-Taylor and
Martin Anthony (eds.), Computational Learning Theory:
EUROCOLT'93. Oxford University Press, 1994. (ISBN 0 19 853492
2)
- Martin Anthony and Norman
Biggs, Computational learning theory for artificial neural networks.
In Mathematical Approaches to Neural Networks (ed. J.G.
Taylor), North-Holland Mathematical Library, North-Holland
(Elsevier), 1993, 25--63. (pdf | ps)
- Martin Anthony and John
Shawe-Taylor, Bounds on the complexity of testing and loading
neurons. In ICANN'93: Proceedings of the International
Conference on Artificial Neural Networks, 1993.
Springer-Verlag.
- Martin Anthony and Sean
B. Holden, On the power of linearly weighted neural networks. In ICANN'93:
Proceedings of the International Conference on Artificial Neural
Networks, 1993. Springer-Verlag.
- Martin Anthony and John
Shawe-Taylor, Using the perceptron algorithm to find consistent
hypotheses. Combinatorics, Probability and Computing, 4(2)
(1993): 385--387. (pdf | ps)
- Martin Anthony and Sean
B. Holden, On the power of polynomial discriminators and radial
basis function networks. In Proceedings of the Sixth Annual
Workshop on Computational Learning Theory, Santa Cruz, CA,
1993, 158--164, ACM Press.
- Martin Anthony and John
Shawe-Taylor, A result of Vapnik with applications, Discrete
Applied Mathematics, 47 (1993): 207--217. (pdf
| ps)
- John Shawe-Taylor,
Martin Anthony and Norman Biggs, Bounding sample-size with the
Vapnik-Chervonenkis dimension, Discrete Applied Mathematics,
42 (1), 1993, 65--73. (pdf | ps)
- Martin Anthony and
Norman Biggs, The mean chromatic number of paths and cycles. Discrete
Mathematics 120 (1993): 227-231.
- Martin Anthony and Norman Biggs, Computational
Learning Theory: An Introduction, Cambridge
University Press, Cambridge, UK, 1992. Reprinted in paperback,
1997 (h/b ISBN 0 521 59922 9, p/b
ISBN 0 521 41603 5.)
- John Shawe-Taylor, Martin
Anthony and Walter Kern, Classes of feedforward neural networks and
their circuit complexity, Neural Networks 5 (6), 1992:
971--977.
- Martin Anthony, Graham Brightwell, Dave Cohen and
John Shawe-Taylor. On exact specification by examples. In Proceedings
of the Fifth Annual Workshop on Computational Learning Theory,
Santa Cruz, CA, 1992, 311-318, ACM Press.
- Martin Anthony, On
deviation of relative frequencies from probabilities. LSE
Mathematics Preprint Series LSE-MPS-2, 1991.
- John Shawe-Taylor and
Martin Anthony, Sample sizes for multiple output threshold networks,
Network: Computation in Neural Systems, 2 (1991): 107--117.
- Martin Anthony, Uniform
Convergence
and Learnability. PhD
thesis.,University
of
London 1991.
- Martin Anthony, Norman
Biggs and John Shawe-Taylor, The learnability of formal concepts, in
COLT 90, Proceedings of the Third Annual Workshop on
Computational Learning Theory, Rochester NY, August 1990,
246--257. Published by Morgan Kauffman.
- Martin Anthony, Keith
Martin, Jennifer Seberry and Peter Wild. Some remarks on
authentication systems. In Advances in Cryptology: Auscrypt'90,
Lecture Notes in Computer Science, 453 (1990), 122--139.
- Martin Anthony,
Computing chromatic polynomials, Ars
Combinatoria 90 (1990), 216-220.
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