Joel Ratsaby - RankMe

58 papers A* 2A 1B 5C 2Misc 3Journal 37Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	C	`conf`	Multi-GPU Processing of Unstructured Data for Machine Learning. ISC Joel Ratsaby, Alexander Timashkov
2023	B	`conf`	Accelerating the LZ-complexity algorithm. ICPADS Joel Ratsaby, Alexander Timashkov
2023	J	`jnl`	Learning half-spaces on general infinite spaces equipped with a distance function. Inf. Comput. Joel Ratsaby
2020	J	`jnl`	Large-width machine learning algorithm. Prog. Artif. Intell. Martin Anthony, Joel Ratsaby
2018	J	`jnl`	Large width nearest prototype classification on general distance spaces. Theor. Comput. Sci. Martin Anthony, Joel Ratsaby
2018	J	`jnl`	Large-width bounds for learning half-spaces on distance spaces. Discret. Appl. Math. Martin Anthony, Joel Ratsaby
2018	A	`conf`	On how complexity affects the stability of a predictor. AISTATS Joel Ratsaby
2017	J	`jnl`	Classification based on prototypes with spheres of influence. Inf. Comput. Martin Anthony, Joel Ratsaby
2016	J	`jnl`	Multi-category classifiers and sample width. J. Comput. Syst. Sci. Martin Anthony, Joel Ratsaby
2016	—	`ch.`	PAC Learning. Encyclopedia of Algorithms Joel Ratsaby
2015	B	`conf`	A Parallel Distributed Processing Algorithm for Image Feature Extraction. IDA Alexander Belousov, Joel Ratsaby
2015	J	`jnl`	A probabilistic approach to case-based inference. Theor. Comput. Sci. Martin Anthony, Joel Ratsaby
2015	B	`conf`	On complexity and randomness of Markov-chain prediction. ITW Joel Ratsaby
2014	—	`conf`	A New Pseudo-metric for Fuzzy Sets. ICAISC (1) László Kovács, Joel Ratsaby
2014	J	`jnl`	A hybrid classifier based on boxes and nearest neighbors. Discret. Appl. Math. Martin Anthony, Joel Ratsaby
2014	J	`jnl`	Learning bounds via sample width for classifiers on finite metric spaces. Theor. Comput. Sci. Martin Anthony, Joel Ratsaby
2013	B	`conf`	Machine Learning for Image Classification and Clustering Using a Universal Distance Measure. SISAP Uzi Chester, Joel Ratsaby
2013	J	`jnl`	Machine learning on images using a string-distance CoRR Uzi Chester, Joel Ratsaby
2013	—	`conf`	Maximal-margin case-based inference. UKCI Martin Anthony, Joel Ratsaby
2013	—	`conf`	Quantifying accuracy of learning via sample width. FOCI Martin Anthony, Joel Ratsaby
2012	J	`jnl`	Analysis of a multi-category classifier. Discret. Appl. Math. Martin Anthony, Joel Ratsaby
2012	J	`jnl`	Robust cutpoints in the logical analysis of numerical data. Discret. Appl. Math. Martin Anthony, Joel Ratsaby
2012	Misc	`conf`	The performance of a new hybrid classifier based on boxes and nearest neighbors. ISAIM Martin Anthony, Joel Ratsaby
2011	J	`jnl`	On the sysRatio and its critical point. Math. Comput. Model. Joel Ratsaby
2010	J	`jnl`	Descriptive-complexity based distance for fuzzy sets CoRR László Kovács, Joel Ratsaby
2010	J	`jnl`	Maximal width learning of binary functions. Theor. Comput. Sci. Martin Anthony, Joel Ratsaby
2010	J	`jnl`	On the algorithmic complexity of static structures. J. Syst. Sci. Complex. Joel Ratsaby, Joël Chaskalovic
2010	J	`jnl`	Prediction by Compression CoRR Joel Ratsaby
2009	J	`jnl`	Combinatorial information distance CoRR Joel Ratsaby
2009	J	`jnl`	How random are a learner's mistakes? CoRR Joel Ratsaby
2009	J	`jnl`	Learning, complexity and information density CoRR Joel Ratsaby
2009	J	`jnl`	Random scattering of bits by prediction CoRR Joel Ratsaby
2008	J	`jnl`	Algorithmic complexity and randomness in elastic solids CoRR Joel Ratsaby, Joël Chaskalovic
2008	J	`jnl`	An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory. Entropy Joel Ratsaby
2008	J	`jnl`	An algorithmic complexity interpretation of Lin's third law of information theory CoRR Joel Ratsaby
2008	J	`jnl`	Constrained versions of Sauer's lemma. Discret. Appl. Math. Joel Ratsaby
2008	J	`jnl`	Information Width CoRR Joel Ratsaby
2008	J	`jnl`	On the Complexity of Binary Samples CoRR Joel Ratsaby
2008	J	`jnl`	On the complexity of binary samples. Ann. Math. Artif. Intell. Joel Ratsaby
2008	J	`jnl`	On the complexity of constrained VC-classes. Discret. Appl. Math. Joel Ratsaby
2008	—	`ch.`	PAC Learning. Encyclopedia of Algorithms Joel Ratsaby
2008	J	`jnl`	VC-Dimensions of Random Function Classes. Discret. Math. Theor. Comput. Sci. Bernard Ycart, Joel Ratsaby
2007	—	`conf`	Information Efficiency. SOFSEM (1) Joel Ratsaby
2007	J	`jnl`	The VC dimension of k-uniform random hypergraphs. Random Struct. Algorithms Bernard Ycart, Joel Ratsaby
2006	J	`jnl`	Complexity of hyperconcepts. Theor. Comput. Sci. Joel Ratsaby
2006	Misc	`conf`	On the Combinatorial Representation of Information. COCOON Joel Ratsaby
2004	Misc	`conf`	On the Complexity of Samples for Learning. COCOON Joel Ratsaby
2003	B	`conf`	A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation. ALT Joel Ratsaby
2003	J	`jnl`	On learning multicategory classification with sample queries. Inf. Comput. Joel Ratsaby
2000	C	`conf`	On partially blind learning complexity. ISCAS Joel Ratsaby, Santosh S. Venkatesh
1999	J	`jnl`	On the Learnability of Rich Function Classes. J. Comput. Syst. Sci. Joel Ratsaby, Vitaly Maiorov
1998	J	`jnl`	Incremental Learning With Sample Queries. IEEE Trans. Pattern Anal. Mach. Intell. Joel Ratsaby
1998	J	`jnl`	The Degree of Approximation of Sets in Euclidean Space Using Sets with Bounded Vapnik-Chervonenkis Dimension. Discret. Appl. Math. Vitaly Maiorov, Joel Ratsaby
1997	—	`conf`	An Incremental Nearest Neighbor Algorithm with Queries. NIPS Joel Ratsaby
1997	—	`conf`	Generalization of the PAC-Model for Learning with Partial Information. EuroCOLT Joel Ratsaby, Vitaly Maiorov
1997	J	`jnl`	On the Value of Partial Information for Learning from Examples. J. Complex. Joel Ratsaby, Vitaly Maiorov
1996	A*	`conf`	Towards Robust Model Selection Using Estimation and Approximation Error Bounds. COLT Joel Ratsaby, Ron Meir, Vitaly Maiorov
1995	A*	`conf`	Learning from a Mixture of Labeled and Unlabeled Examples with Parametric Side Information. COLT Joel Ratsaby, Santosh S. Venkatesh