Joel Ratsaby

According to our database1, Joel Ratsaby authored at least 51 papers between 1995 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2018
Large width nearest prototype classification on general distance spaces.
Theor. Comput. Sci., 2018

Large-width bounds for learning half-spaces on distance spaces.
Discrete Applied Mathematics, 2018

On how complexity affects the stability of a predictor.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Classification based on prototypes with spheres of influence.
Inf. Comput., 2017

2016
PAC Learning.
Encyclopedia of Algorithms, 2016

Multi-category classifiers and sample width.
J. Comput. Syst. Sci., 2016

2015
A probabilistic approach to case-based inference.
Theor. Comput. Sci., 2015

On complexity and randomness of Markov-chain prediction.
Proceedings of the 2015 IEEE Information Theory Workshop, 2015

A Parallel Distributed Processing Algorithm for Image Feature Extraction.
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

2014
Learning bounds via sample width for classifiers on finite metric spaces.
Theor. Comput. Sci., 2014

A hybrid classifier based on boxes and nearest neighbors.
Discrete Applied Mathematics, 2014

A New Pseudo-metric for Fuzzy Sets.
Proceedings of the Artificial Intelligence and Soft Computing, 2014

2013
Machine learning on images using a string-distance
CoRR, 2013

Maximal-margin case-based inference.
Proceedings of the 13th UK Workshop on Computational Intelligence, 2013

Machine Learning for Image Classification and Clustering Using a Universal Distance Measure.
Proceedings of the Similarity Search and Applications - 6th International Conference, 2013

Quantifying accuracy of learning via sample width.
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2013

2012
Analysis of a multi-category classifier.
Discrete Applied Mathematics, 2012

Robust cutpoints in the logical analysis of numerical data.
Discrete Applied Mathematics, 2012

The performance of a new hybrid classifier based on boxes and nearest neighbors.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2012

2011
On the sysRatio and its critical point.
Mathematical and Computer Modelling, 2011

2010
Maximal width learning of binary functions.
Theor. Comput. Sci., 2010

On the algorithmic complexity of static structures.
J. Systems Science & Complexity, 2010

Descriptive-complexity based distance for fuzzy sets
CoRR, 2010

Prediction by Compression
CoRR, 2010

2009
Random scattering of bits by prediction
CoRR, 2009

Learning, complexity and information density
CoRR, 2009

Combinatorial information distance
CoRR, 2009

How random are a learner's mistakes?
CoRR, 2009

2008
PAC Learning.
Proceedings of the Encyclopedia of Algorithms - 2008 Edition, 2008

An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory.
Entropy, 2008

VC-Dimensions of Random Function Classes.
Discrete Mathematics & Theoretical Computer Science, 2008

Constrained versions of Sauer's lemma.
Discrete Applied Mathematics, 2008

On the complexity of constrained VC-classes.
Discrete Applied Mathematics, 2008

Algorithmic complexity and randomness in elastic solids
CoRR, 2008

Information Width
CoRR, 2008

On the complexity of binary samples.
Ann. Math. Artif. Intell., 2008

2007
The VC dimension of k-uniform random hypergraphs.
Random Struct. Algorithms, 2007

Information Efficiency.
Proceedings of the SOFSEM 2007: Theory and Practice of Computer Science, 2007

2006
Complexity of hyperconcepts.
Theor. Comput. Sci., 2006

On the Combinatorial Representation of Information.
Proceedings of the Computing and Combinatorics, 12th Annual International Conference, 2006

2004
On the Complexity of Samples for Learning.
Proceedings of the Computing and Combinatorics, 10th Annual International Conference, 2004

2003
On learning multicategory classification with sample queries.
Inf. Comput., 2003

A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation.
Proceedings of the Algorithmic Learning Theory, 14th International Conference, 2003

1999
On the Learnability of Rich Function Classes.
J. Comput. Syst. Sci., 1999

1998
Incremental Learning With Sample Queries.
IEEE Trans. Pattern Anal. Mach. Intell., 1998

The Degree of Approximation of Sets in Euclidean Space Using Sets with Bounded Vapnik-Chervonenkis Dimension.
Discrete Applied Mathematics, 1998

1997
On the Value of Partial Information for Learning from Examples.
J. Complexity, 1997

An Incremental Nearest Neighbor Algorithm with Queries.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Generalization of the PAC-Model for Learning with Partial Information.
Proceedings of the Computational Learning Theory, Third European Conference, 1997

1996
Towards Robust Model Selection Using Estimation and Approximation Error Bounds.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
Learning from a Mixture of Labeled and Unlabeled Examples with Parametric Side Information.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995


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