Martin Anthony

According to our database, Martin Anthony authored at least 63 papers between 1990 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2020

Large-width machine learning algorithm.

Martin Anthony, Joel Ratsaby

Prog. Artif. Intell., 2020

2018

Large width nearest prototype classification on general distance spaces.

Martin Anthony, Joel Ratsaby

Theor. Comput. Sci., 2018

Large-width bounds for learning half-spaces on distance spaces.

Martin Anthony, Joel Ratsaby

Discret. Appl. Math., 2018

2017

Quadratic reformulations of nonlinear binary optimization problems.

Martin Anthony, Endre Boros, Yves Crama, Aritanan Gruber

Math. Program., 2017

Classification based on prototypes with spheres of influence.

Martin Anthony, Joel Ratsaby

Inf. Comput., 2017

2016

Multi-category classifiers and sample width.

Martin Anthony, Joel Ratsaby

J. Comput. Syst. Sci., 2016

Quadratization of symmetric pseudo-Boolean functions.

Martin Anthony, Endre Boros, Yves Crama, Aritanan Gruber

Discret. Appl. Math., 2016

2015

A probabilistic approach to case-based inference.

Martin Anthony, Joel Ratsaby

Theor. Comput. Sci., 2015

2014

Learning bounds via sample width for classifiers on finite metric spaces.

Martin Anthony, Joel Ratsaby

Theor. Comput. Sci., 2014

A hybrid classifier based on boxes and nearest neighbors.

Martin Anthony, Joel Ratsaby

Discret. Appl. Math., 2014

2013

Maximal-margin case-based inference.

Martin Anthony, Joel Ratsaby

Proceedings of the 13th UK Workshop on Computational Intelligence, 2013

Quantifying accuracy of learning via sample width.

Martin Anthony, Joel Ratsaby

Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2013

2012

Analysis of a multi-category classifier.

Martin Anthony, Joel Ratsaby

Discret. Appl. Math., 2012

Robust cutpoints in the logical analysis of numerical data.

Martin Anthony, Joel Ratsaby

Discret. Appl. Math., 2012

Generalization error bounds for the logical analysis of data.

Martin Anthony

Discret. Appl. Math., 2012

The performance of a new hybrid classifier based on boxes and nearest neighbors.

Martin Anthony, Joel Ratsaby

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2012

2011

A new imputation method for incomplete binary data.

Munevver Mine Subasi, Ersoy Subasi, Martin Anthony, Peter L. Hammer

Discret. Appl. Math., 2011

2010

Maximal width learning of binary functions.

Martin Anthony, Joel Ratsaby

Theor. Comput. Sci., 2010

Decision Lists and Related Classes of Boolean Functions.

Martin Anthony, Yves Crama, Peter L. Hammer

Proceedings of the Boolean Models and Methods in Mathematics, 2010

Neural Networks and Boolean Functions.

Martin Anthony, Yves Crama, Peter L. Hammer

Proceedings of the Boolean Models and Methods in Mathematics, 2010

Probabilistic Learning and Boolean Functions.

Martin Anthony, Yves Crama, Peter L. Hammer

Proceedings of the Boolean Models and Methods in Mathematics, 2010

2009

On Constructing Threshold Networks for Pattern Classification.

Martin Anthony

Proceedings of the Constructive Neural Networks, 2009

Using a similarity measure for credible classification.

Munevver Mine Subasi, Ersoy Subasi, Martin Anthony, Peter L. Hammer

Discret. Appl. Math., 2009

2008

Preface.

Martin Anthony, Endre Boros, Alexander Kogan

Discret. Appl. Math., 2008

Aspects of discrete mathematics and probability in the theory of machine learning.

Martin Anthony

Discret. Appl. Math., 2008

2007

On the generalization error of fixed combinations of classifiers.

Martin Anthony

J. Comput. Syst. Sci., 2007

2006

The influence of oppositely classified examples on the generalization complexity of Boolean functions.

Leonardo Franco, Martin Anthony

IEEE Trans. Neural Networks, 2006

A Boolean measure of similarity.

Martin Anthony, Peter L. Hammer

Discret. Appl. Math., 2006

Preface.

Martin Anthony, Endre Boros, Peter L. Hammer, Alexander Kogan

Discret. Appl. Math., 2006

A New Constructive Approach for Creating All Linearly Separable (Threshold) Functions.

Leonardo Franco, José Luis Subirats, Martin Anthony, José M. Jerez

Proceedings of the International Joint Conference on Neural Networks, 2006

2004

Generalization Error Bounds for Threshold Decision Lists.

Martin Anthony

J. Mach. Learn. Res., 2004

Partitioning points by parallel planes.

Martin Anthony

Discret. Math., 2004

Introduction to special volume of Discrete Applied Mathematics.

Martin Anthony, Endre Boros, Peter L. Hammer, Alexander Kogan

Discret. Appl. Math., 2004

Some connections between learning and optimization.

Martin Anthony

Discret. Appl. Math., 2004

On data classification by iterative linear partitioning.

Martin Anthony

Discret. Appl. Math., 2004

On a generalization complexity measure for Boolean functions.

Leonardo Franco, Martin Anthony

Proceedings of the IEEE International Joint Conference on Neural Networks, 2004

On learning a function of perceptrons.

Martin Anthony

Proceedings of the IEEE International Joint Conference on Neural Networks, 2004

2002

Mathematical Modelling of Generalization.

Martin Anthony

Proceedings of the Neural Nets, 13th Italian Workshop on Neural Nets, 2002

Neural Network Learning - Theoretical Foundations.

Martin Anthony, Peter L. Bartlett

Cambridge University Press, ISBN: 978-0-521-57353-5, 2002

2000

Function Learning From Interpolation.

Martin Anthony, Peter L. Bartlett

Comb. Probab. Comput., 2000

1999

Accuracy of Techniques for the Logical Analysis of Data.

Martin Anthony

Discret. Appl. Math., 1999

1998

Structural Risk Minimization Over Data-Dependent Hierarchies.

John Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson, Martin Anthony

IEEE Trans. Inf. Theory, 1998

Probabilistic 'generalization' of functions and dimension-based uniform convergence results.

Martin Anthony

Stat. Comput., 1998

Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis.

Martin Anthony, Sean B. Holden

Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997

A Sufficient Condition for Polynomial Distribution-dependent Learnability.

Martin Anthony, John Shawe-Taylor

Discret. Appl. Math., 1997

1996

Valid Generalisation from Approximate Interpolation.

Martin Anthony, Peter L. Bartlett, Yuval Ishai, John Shawe-Taylor

Comb. Probab. Comput., 1996

A Framework for Structural Risk Minimisation.

John Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson, Martin Anthony

Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995

The vapnik-chervonenkis dimension of a random graph.

Martin Anthony, Graham R. Brightwell, Colin Cooper

Discret. Math., 1995

On Specifying Boolean Functions by Labelled Examples.

Martin Anthony, Graham R. Brightwell, John Shawe-Taylor

Discret. Appl. Math., 1995

Classification by Polynomial Surfaces.

Martin Anthony

Discret. Appl. Math., 1995

Interpolation and Learning in Artificial Neural Networks.

Martin Anthony

Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

1994

On the mean chromatic number.

Martin Anthony

Discret. Math., 1994

Quantifying Generalization in Linearly Weighted Neural Networks.

Martin Anthony, Sean B. Holden

Complex Syst., 1994

1993

The mean chromatic number of paths and cycles.

Martin Anthony, Norman Biggs

Discret. Math., 1993

Bounding Sample Size with the Vapnik-Chervonenkis Dimension.

John Shawe-Taylor, Martin Anthony, Norman Biggs

Discret. Appl. Math., 1993

A Result of Vapnik with Applications.

Martin Anthony, John Shawe-Taylor

Discret. Appl. Math., 1993

Using the Perceptron Algorithm to Find Consistent Hypotheses.

Martin Anthony, John Shawe-Taylor

Comb. Probab. Comput., 1993

Valid generalisation of functions from close approximations on a sample.

Martin Anthony, John Shawe-Taylor

Proceedings of the First European Conference on Computational Learning Theory, 1993

On the Power of Polynomial Discriminators and Radial Basis Function Networks.

Martin Anthony, Sean B. Holden

Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992

Classes of feedforward neural networks and their circuit complexity.

John Shawe-Taylor, Martin Anthony, Walter Kern

Neural Networks, 1992

On Exact Specification by Examples.

Martin Anthony, Graham R. Brightwell, David A. Cohen, John Shawe-Taylor

Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

1990

The Learnability of Formal Concepts.

Martin Anthony, Norman Biggs, John Shawe-Taylor

Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

Some Remarks on Authentication Systems.

Martin Anthony, Keith M. Martin, Jennifer Seberry, Peter R. Wild

Proceedings of the Advances in Cryptology, 1990