Some Remarks on Authentication Systems. - Martin Anthony; Keith M. Martin; Jennifer Seberry; Peter R. Wild (AUSCRYPT, 1990)

The Learnability of Formal Concepts. - Martin Anthony; Norman Biggs; John Shawe-Taylor (COLT, 1990)

On Exact Specification by Examples. - Martin Anthony; Graham R. Brightwell; David A. Cohen; John Shawe-Taylor (COLT, 1992)

Classes of feedforward neural networks and their circuit complexity. - John Shawe-Taylor; Martin Anthony; Walter Kern (Neural Networks, 1992)

On the Power of Polynomial Discriminators and Radial Basis Function Networks. - Martin Anthony; Sean B. Holden (COLT, 1993)

Valid generalisation of functions from close approximations on a sample. - Martin Anthony; John Shawe-Taylor (EuroCOLT, 1993)

Using the Perceptron Algorithm to Find Consistent Hypotheses. - Martin Anthony; John Shawe-Taylor (Comb. Probab. Comput., 1993)

A Result of Vapnik with Applications. - Martin Anthony; John Shawe-Taylor (Discret. Appl. Math., 1993)

Bounding Sample Size with the Vapnik-Chervonenkis Dimension. - John Shawe-Taylor; Martin Anthony; Norman Biggs (Discret. Appl. Math., 1993)

The mean chromatic number of paths and cycles. - Martin Anthony; Norman Biggs (Discret. Math., 1993)

Quantifying Generalization in Linearly Weighted Neural Networks. - Martin Anthony; Sean B. Holden (Complex Syst., 1994)

On the mean chromatic number. - Martin Anthony (Discret. Math., 1994)

Interpolation and Learning in Artificial Neural Networks. - Martin Anthony (ICNN, 1995)

Classification by Polynomial Surfaces. - Martin Anthony (Discret. Appl. Math., 1995)

On Specifying Boolean Functions by Labelled Examples. - Martin Anthony; Graham R. Brightwell; John Shawe-Taylor (Discret. Appl. Math., 1995)

The vapnik-chervonenkis dimension of a random graph. - Martin Anthony; Graham R. Brightwell; Colin Cooper (Discret. Math., 1995)

A Framework for Structural Risk Minimisation. - John Shawe-Taylor; Peter L. Bartlett; Robert C. Williamson; Martin Anthony (COLT, 1996)

Valid Generalisation from Approximate Interpolation. - Martin Anthony; Peter L. Bartlett; Yuval Ishai; John Shawe-Taylor (Comb. Probab. Comput., 1996)

A Sufficient Condition for Polynomial Distribution-dependent Learnability. - Martin Anthony; John Shawe-Taylor (Discret. Appl. Math., 1997)

Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis. - Martin Anthony; Sean B. Holden (COLT, 1998)

Probabilistic 'generalization' of functions and dimension-based uniform convergence results. - Martin Anthony (Stat. Comput., 1998)

Structural Risk Minimization Over Data-Dependent Hierarchies. - John Shawe-Taylor; Peter L. Bartlett; Robert C. Williamson; Martin Anthony (IEEE Trans. Inf. Theory, 1998)

Accuracy of Techniques for the Logical Analysis of Data. - Martin Anthony (Discret. Appl. Math., 1999)

Function Learning From Interpolation. - Martin Anthony; Peter L. Bartlett (Comb. Probab. Comput., 2000)

Neural Network Learning - Theoretical Foundations. - Martin Anthony; Peter L. Bartlett (Cambridge University Press, 2002)

Mathematical Modelling of Generalization. - Martin Anthony (WIRN, 2002)

On learning a function of perceptrons. - Martin Anthony (IJCNN, 2004)

On a generalization complexity measure for Boolean functions. - Leonardo Franco; Martin Anthony (IJCNN, 2004)

On data classification by iterative linear partitioning. - Martin Anthony (Discret. Appl. Math., 2004)

Some connections between learning and optimization. - Martin Anthony (Discret. Appl. Math., 2004)

Introduction to special volume of Discrete Applied Mathematics. - Martin Anthony; Endre Boros; Peter L. Hammer; Alexander Kogan (Discret. Appl. Math., 2004)

Partitioning points by parallel planes. - Martin Anthony (Discret. Math., 2004)

Generalization Error Bounds for Threshold Decision Lists. - Martin Anthony (J. Mach. Learn. Res., 2004)

A New Constructive Approach for Creating All Linearly Separable (Threshold) Functions. - Leonardo Franco; José Luis Subirats; Martin Anthony; José M. Jerez (IJCNN, 2006)

Preface. - Martin Anthony; Endre Boros; Peter L. Hammer; Alexander Kogan (Discret. Appl. Math., 2006)

A Boolean measure of similarity. - Martin Anthony; Peter L. Hammer (Discret. Appl. Math., 2006)

The influence of oppositely classified examples on the generalization complexity of Boolean functions. - Leonardo Franco; Martin Anthony (IEEE Trans. Neural Networks, 2006)

On the generalization error of fixed combinations of classifiers. - Martin Anthony (J. Comput. Syst. Sci., 2007)

Aspects of discrete mathematics and probability in the theory of machine learning. - Martin Anthony (Discret. Appl. Math., 2008)

Preface. - Martin Anthony; Endre Boros; Alexander Kogan (Discret. Appl. Math., 2008)

Using a similarity measure for credible classification. - Munevver Mine Subasi; Ersoy Subasi; Martin Anthony; Peter L. Hammer (Discret. Appl. Math., 2009)

On Constructing Threshold Networks for Pattern Classification. - Martin Anthony (Constructive Neural Networks, 2009)

Probabilistic Learning and Boolean Functions. - Martin Anthony; Yves Crama; Peter L. Hammer (Boolean Models and Methods, 2010)

Neural Networks and Boolean Functions. - Martin Anthony; Yves Crama; Peter L. Hammer (Boolean Models and Methods, 2010)

Decision Lists and Related Classes of Boolean Functions. - Martin Anthony; Yves Crama; Peter L. Hammer (Boolean Models and Methods, 2010)

Maximal width learning of binary functions. - Martin Anthony; Joel Ratsaby (Theor. Comput. Sci., 2010)

A new imputation method for incomplete binary data. - Munevver Mine Subasi; Ersoy Subasi; Martin Anthony; Peter L. Hammer (Discret. Appl. Math., 2011)

The performance of a new hybrid classifier based on boxes and nearest neighbors. - Martin Anthony; Joel Ratsaby (ISAIM, 2012)

Generalization error bounds for the logical analysis of data. - Martin Anthony (Discret. Appl. Math., 2012)

Robust cutpoints in the logical analysis of numerical data. - Martin Anthony; Joel Ratsaby (Discret. Appl. Math., 2012)

Analysis of a multi-category classifier. - Martin Anthony; Joel Ratsaby (Discret. Appl. Math., 2012)

Quantifying accuracy of learning via sample width. - Martin Anthony; Joel Ratsaby (FOCI, 2013)

Maximal-margin case-based inference. - Martin Anthony; Joel Ratsaby (UKCI, 2013)

A hybrid classifier based on boxes and nearest neighbors. - Martin Anthony; Joel Ratsaby (Discret. Appl. Math., 2014)

Learning bounds via sample width for classifiers on finite metric spaces. - Martin Anthony; Joel Ratsaby (Theor. Comput. Sci., 2014)

A probabilistic approach to case-based inference. - Martin Anthony; Joel Ratsaby (Theor. Comput. Sci., 2015)

Quadratization of symmetric pseudo-Boolean functions. - Martin Anthony; Endre Boros; Yves Crama; Aritanan Gruber (Discret. Appl. Math., 2016)

Multi-category classifiers and sample width. - Martin Anthony; Joel Ratsaby (J. Comput. Syst. Sci., 2016)

Classification based on prototypes with spheres of influence. - Martin Anthony; Joel Ratsaby (Inf. Comput., 2017)

Quadratic reformulations of nonlinear binary optimization problems. - Martin Anthony; Endre Boros; Yves Crama; Aritanan Gruber (Math. Program., 2017)

Large-width bounds for learning half-spaces on distance spaces. - Martin Anthony; Joel Ratsaby (Discret. Appl. Math., 2018)

Large width nearest prototype classification on general distance spaces. - Martin Anthony; Joel Ratsaby (Theor. Comput. Sci., 2018)

Large-width machine learning algorithm. - Martin Anthony; Joel Ratsaby (Prog. Artif. Intell., 2020)