Joel Ratsaby

发表

Towards robust model selection using estimation and approximation error bounds

Ron Meir, Joel Ratsaby, Vitaly Maiorov, 1996, COLT '96.

Information Width pdf

Joel Ratsaby, Joel Ratsaby, 2008, ArXiv.

Machine Learning for Image Classification and Clustering Using a Universal Distance Measure

Joel Ratsaby, Uzi Chester, 2013, SISAP.

Information Efficiency

Joel Ratsaby, 2007, SOFSEM.

Combinatorial information distance pdf

Joel Ratsaby, 2009, ArXiv.

An FPGA-based pattern classifier using data compression

Joel Ratsaby, Denis Zavielov, Joel Ratsaby, 2010, 2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel.

PAC Learning

Joel Ratsaby, 2008, Encyclopedia of Algorithms.

On complexity and randomness of Markov-chain prediction

Joel Ratsaby, 2015, 2015 IEEE Information Theory Workshop (ITW).

A probabilistic approach to case-based inference

Martin Anthony, Joel Ratsaby, M. Anthony, 2015, Theor. Comput. Sci..

Parallelizing the Large-Width learning algorithm

Joel Ratsaby, Alon Sabaty, 2018, 2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE).

A hybrid classifier based on boxes and nearest neighbors

Martin Anthony, Joel Ratsaby, M. Anthony, 2014, Discret. Appl. Math..

Massively parallel computations of the LZ-complexity of strings

Joel Ratsaby, Alexander Belousov, 2014, 2014 IEEE 28th Convention of Electrical & Electronics Engineers in Israel (IEEEI).

Analysis of a multi-category classifier

Martin Anthony, Joel Ratsaby, 2012, Discret. Appl. Math..

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

Martin Anthony, Joel Ratsaby, 2018, Discret. Appl. Math..

How random are a learner's mistakes? pdf

Joel Ratsaby, 2009, ArXiv.

Multi-category classifiers and sample width

Martin Anthony, Joel Ratsaby, 2016, J. Comput. Syst. Sci..

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

Martin Anthony, Joel Ratsaby, M. Anthony, 2012, ISAIM.

Large width nearest prototype classification on general distance spaces

Martin Anthony, Joel Ratsaby, M. Anthony, 2018, Theor. Comput. Sci..

On the Complexity of Samples for Learning

Joel Ratsaby, 2004, COCOON.

Machine learning on images using a string-distance pdf

Joel Ratsaby, Uzi Chester, 2013, ArXiv.

Maximal-margin case-based inference

Martin Anthony, Joel Ratsaby, M. Anthony, 2013, 2013 13th UK Workshop on Computational Intelligence (UKCI).

On the sysRatio and its critical point

Joel Ratsaby, 2011, Math. Comput. Model..

On the Learnability of Rich Function Classes

Joel Ratsaby, Vitaly Maiorov, Joel Ratsaby, 1999, J. Comput. Syst. Sci..

On how complexity affects the stability of a predictor

Joel Ratsaby, 2018, AISTATS.

On the algorithmic complexity of static structures

Joel Ratsaby, Joël Chaskalovic, 2010, J. Syst. Sci. Complex..

An Incremental Nearest Neighbor Algorithm with Queries

Joel Ratsaby, Joel Ratsaby, 1997, NIPS.

Algorithmic complexity and randomness in elastic solids pdf

Joel Ratsaby, Joël Chaskalovic, 2008, ArXiv.

Quantifying accuracy of learning via sample width

Martin Anthony, Joel Ratsaby, 2013, 2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI).

Learning from a mixture of labeled and unlabeled examples with parametric side information

Santosh S. Venkatesh, Joel Ratsaby, S. Venkatesh, 1995, COLT '95.

A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation

Joel Ratsaby, 2003, ALT.

A New Pseudo-metric for Fuzzy Sets

László Kovács, Joel Ratsaby, 2014, ICAISC.

Large margin case-based reasoning

Martin Anthony, Joel Ratsaby, M. Anthony, 2013 .

On the complexity of constrained VC-classes

Joel Ratsaby, Joel Ratsaby, 2008, Discret. Appl. Math..

On the Value of Partial Information for Learning from Examples

Joel Ratsaby, Vitaly Maiorov, Joel Ratsaby, 1997, J. Complex..

Learning bounds via sample width for classifiers on finite metric spaces

Martin Anthony, Joel Ratsaby, 2014, Theor. Comput. Sci..

PAC Learning

Joel Ratsaby, 2016, Encyclopedia of Algorithms.

Information and

Martin Anthony, Joel Ratsaby, M. Anthony, 2017 .

On learning multicategory classification with sample queries

Joel Ratsaby, Joel Ratsaby, 2003, Inf. Comput..

Generalization of the PAC-Model for Learning with Partial Information

Joel Ratsaby, Vitaly Maiorov, Joel Ratsaby, 1997, EuroCOLT.

Maximal width learning of binary functions

Martin Anthony, Joel Ratsaby, 2010, Theor. Comput. Sci..

The VC dimension of k-uniform random hypergraphs

Joel Ratsaby, Bernard Ycart, 2007, Random Struct. Algorithms.

Large-width machine learning algorithm

Martin Anthony, Joel Ratsaby, M. Anthony, 2020, Progress in Artificial Intelligence.

On the Combinatorial Representation of Information

Joel Ratsaby, 2006, COCOON.

Learning, complexity and information density pdf

Joel Ratsaby, 2009, ArXiv.

Random scattering of bits by prediction pdf

Joel Ratsaby, Joel Ratsaby, 2009, ArXiv.

Complexity of hyperconcepts

Joel Ratsaby, Joel Ratsaby, 2006, Theor. Comput. Sci..

Constrained versions of Sauer's lemma

Joel Ratsaby, Joel Ratsaby, 2008, Discret. Appl. Math..

VC-Dimensions of Random Function Classes

Joel Ratsaby, Bernard Ycart, Joel Ratsaby, 2008, Discret. Math. Theor. Comput. Sci..

Prediction by Compression pdf

Joel Ratsaby, Joel Ratsaby, 2010, ArXiv.

Robust cutpoints in the logical analysis of numerical data

Martin Anthony, Joel Ratsaby, 2012, Discret. Appl. Math..

Incremental Learning With Sample Queries

Joel Ratsaby, Joel Ratsaby, 1998, IEEE Trans. Pattern Anal. Mach. Intell..

An algorithmic complexity interpretation of Lin's third law of information theory pdf

Joel Ratsaby, 2008, Entropy.

A Parallel Distributed Processing Algorithm for Image Feature Extraction

Joel Ratsaby, Alexander Belousov, 2015, IDA.

On the complexity of binary samples

Joel Ratsaby, 2008, Annals of Mathematics and Artificial Intelligence.

The Degree of Approximation of Sets in Euclidean Space Using Sets with Bounded Vapnik-Chervonenkis Dimension

Joel Ratsaby, Vitaly Maiorov, Joel Ratsaby, 1998, Discret. Appl. Math..

Descriptive-complexity based distance for fuzzy sets pdf

László Kovács, Joel Ratsaby, 2010, ArXiv.

Finite Sample Size Results for Robust Model Selection; Application to Neural Networks

Ron Meir, Joel Ratsaby, 1995 .

Interaction of a self vibrating beam with chaotic external forces

Joel Ratsaby, Joël Chaskalovic, 2010 .

Sample width for multi-category classifiers

Martin Anthony, Joel Ratsaby, 2012 .

Learning on finite metric spaces

Martin Anthony, Joel Ratsaby, 2012 .

Estimate of the number of restricted integer-partitions

Joel Ratsaby, 2008 .

On the randomness in learning

Joel Ratsaby, 2009, 2009 IEEE International Conference on Computational Cybernetics (ICCC).

Some Consequences of the Complexity of Intelligent Prediction

Joel Ratsaby, 2010 .

Analysis of Linear Interpolation of Fuzzy Sets with Entropy-based Distances

László Kovács, Joel Ratsaby, 2013 .

An empirical study of the complexity and randomness of prediction error sequences

Joel Ratsaby, Joel Ratsaby, 2011 .

Using boxes and proximity to classify data into several categories

Martin Anthony, Joel Ratsaby, M. Anthony, 2012 .