Learning from a Mixture of Labeled and Unlabeled Examples with Parametric Side Information. - Joel Ratsaby; Santosh S. Venkatesh (COLT, 1995)

Towards Robust Model Selection Using Estimation and Approximation Error Bounds. - Joel Ratsaby; Ron Meir; Vitaly Maiorov (COLT, 1996)

Generalization of the PAC-Model for Learning with Partial Information. - Joel Ratsaby; Vitaly Maiorov (EuroCOLT, 1997)

An Incremental Nearest Neighbor Algorithm with Queries. - Joel Ratsaby (NIPS, 1997)

On the Value of Partial Information for Learning from Examples. - Joel Ratsaby; Vitaly Maiorov (J. Complex., 1997)

The Degree of Approximation of Sets in Euclidean Space Using Sets with Bounded Vapnik-Chervonenkis Dimension. - Vitaly Maiorov; Joel Ratsaby (Discret. Appl. Math., 1998)

Incremental Learning With Sample Queries. - Joel Ratsaby (IEEE Trans. Pattern Anal. Mach. Intell., 1998)

On the Learnability of Rich Function Classes. - Joel Ratsaby; Vitaly Maiorov (J. Comput. Syst. Sci., 1999)

On partially blind learning complexity. - Joel Ratsaby; Santosh S. Venkatesh (ISCAS, 2000)

A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation. - Joel Ratsaby (ALT, 2003)

On learning multicategory classification with sample queries. - Joel Ratsaby (Inf. Comput., 2003)

On the Complexity of Samples for Learning. - Joel Ratsaby (COCOON, 2004)

On the Combinatorial Representation of Information. - Joel Ratsaby (COCOON, 2006)

Complexity of hyperconcepts. - Joel Ratsaby (Theor. Comput. Sci., 2006)

Information Efficiency. - Joel Ratsaby (SOFSEM (1), 2007)

The VC dimension of k-uniform random hypergraphs. - Bernard Ycart; Joel Ratsaby (Random Struct. Algorithms, 2007)

On the complexity of binary samples. - Joel Ratsaby (Ann. Math. Artif. Intell., 2008)

Information Width - Joel Ratsaby (CoRR, 2008)

Algorithmic complexity and randomness in elastic solids - Joel Ratsaby; Joël Chaskalovic (CoRR, 2008)

On the complexity of constrained VC-classes. - Joel Ratsaby (Discret. Appl. Math., 2008)

Constrained versions of Sauer's lemma. - Joel Ratsaby (Discret. Appl. Math., 2008)

VC-Dimensions of Random Function Classes. - Bernard Ycart; Joel Ratsaby (Discret. Math. Theor. Comput. Sci., 2008)

An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory. - Joel Ratsaby (Entropy, 2008)

PAC Learning. - Joel Ratsaby (Encyclopedia of Algorithms, 2008)

How random are a learner's mistakes? - Joel Ratsaby (CoRR, 2009)

Combinatorial information distance - Joel Ratsaby (CoRR, 2009)

Learning, complexity and information density - Joel Ratsaby (CoRR, 2009)

Random scattering of bits by prediction - Joel Ratsaby (CoRR, 2009)

Prediction by Compression - Joel Ratsaby (CoRR, 2010)

Descriptive-complexity based distance for fuzzy sets - László Kovács; Joel Ratsaby (CoRR, 2010)

On the algorithmic complexity of static structures. - Joel Ratsaby; Joël Chaskalovic (J. Syst. Sci. Complex., 2010)

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

On the sysRatio and its critical point. - Joel Ratsaby (Math. Comput. Model., 2011)

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

Machine Learning for Image Classification and Clustering Using a Universal Distance Measure. - Uzi Chester; Joel Ratsaby (SISAP, 2013)

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

Machine learning on images using a string-distance - Uzi Chester; Joel Ratsaby (CoRR, 2013)

A New Pseudo-metric for Fuzzy Sets. - László Kovács; Joel Ratsaby (ICAISC (1), 2014)

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 Parallel Distributed Processing Algorithm for Image Feature Extraction. - Alexander Belousov; Joel Ratsaby (IDA, 2015)

On complexity and randomness of Markov-chain prediction. - Joel Ratsaby (ITW, 2015)

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

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

PAC Learning. - Joel Ratsaby (Encyclopedia of Algorithms, 2016)

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

On how complexity affects the stability of a predictor. - Joel Ratsaby (AISTATS, 2018)

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)

Accelerating the LZ-complexity algorithm. - Joel Ratsaby; Alexander Timashkov (ICPADS, 2023)

Learning half-spaces on general infinite spaces equipped with a distance function. - Joel Ratsaby (Inf. Comput., 2023)

Multi-GPU Processing of Unstructured Data for Machine Learning. - Joel Ratsaby; Alexander Timashkov (ISC, 2024)