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Joel Ratsaby
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2020 – today
- 2023
- [j26]Joel Ratsaby
:
Learning half-spaces on general infinite spaces equipped with a distance function. Inf. Comput. 291: 105008 (2023) - [c18]Joel Ratsaby, Alexander Timashkov:
Accelerating the LZ-complexity algorithm. ICPADS 2023: 200-207 - 2020
- [j25]Martin Anthony
, Joel Ratsaby
:
Large-width machine learning algorithm. Prog. Artif. Intell. 9(3): 275-285 (2020)
2010 – 2019
- 2018
- [j24]Martin Anthony
, Joel Ratsaby
:
Large-width bounds for learning half-spaces on distance spaces. Discret. Appl. Math. 243: 73-89 (2018) - [j23]Martin Anthony
, Joel Ratsaby
:
Large width nearest prototype classification on general distance spaces. Theor. Comput. Sci. 738: 65-79 (2018) - [c17]Joel Ratsaby:
On how complexity affects the stability of a predictor. AISTATS 2018: 161-167 - 2017
- [j22]Martin Anthony
, Joel Ratsaby:
Classification based on prototypes with spheres of influence. Inf. Comput. 256: 372-380 (2017) - 2016
- [j21]Martin Anthony
, Joel Ratsaby:
Multi-category classifiers and sample width. J. Comput. Syst. Sci. 82(8): 1223-1231 (2016) - [r2]Joel Ratsaby:
PAC Learning. Encyclopedia of Algorithms 2016: 1497-1500 - 2015
- [j20]Martin Anthony
, Joel Ratsaby:
A probabilistic approach to case-based inference. Theor. Comput. Sci. 589: 61-75 (2015) - [c16]Alexander Belousov, Joel Ratsaby:
A Parallel Distributed Processing Algorithm for Image Feature Extraction. IDA 2015: 61-71 - [c15]Joel Ratsaby:
On complexity and randomness of Markov-chain prediction. ITW 2015: 1-5 - 2014
- [j19]Martin Anthony
, Joel Ratsaby:
A hybrid classifier based on boxes and nearest neighbors. Discret. Appl. Math. 172: 1-11 (2014) - [j18]Martin Anthony
, Joel Ratsaby:
Learning bounds via sample width for classifiers on finite metric spaces. Theor. Comput. Sci. 529: 2-10 (2014) - [c14]László Kovács, Joel Ratsaby:
A New Pseudo-metric for Fuzzy Sets. ICAISC (1) 2014: 205-216 - 2013
- [c13]Martin Anthony
, Joel Ratsaby:
Quantifying accuracy of learning via sample width. FOCI 2013: 84-90 - [c12]Uzi Chester, Joel Ratsaby:
Machine Learning for Image Classification and Clustering Using a Universal Distance Measure. SISAP 2013: 59-72 - [c11]Martin Anthony
, Joel Ratsaby:
Maximal-margin case-based inference. UKCI 2013: 112-119 - [i11]Uzi Chester, Joel Ratsaby:
Machine learning on images using a string-distance. CoRR abs/1305.4204 (2013) - 2012
- [j17]Martin Anthony
, Joel Ratsaby:
Robust cutpoints in the logical analysis of numerical data. Discret. Appl. Math. 160(4-5): 355-364 (2012) - [j16]Martin Anthony
, Joel Ratsaby:
Analysis of a multi-category classifier. Discret. Appl. Math. 160(16-17): 2329-2338 (2012) - [c10]Martin Anthony, Joel Ratsaby:
The performance of a new hybrid classifier based on boxes and nearest neighbors. ISAIM 2012 - 2011
- [j15]Joel Ratsaby:
On the sysRatio and its critical point. Math. Comput. Model. 53(5-6): 939-944 (2011) - 2010
- [j14]Joel Ratsaby, Joël Chaskalovic:
On the algorithmic complexity of static structures. J. Syst. Sci. Complex. 23(6): 1037-1053 (2010) - [j13]Martin Anthony
, Joel Ratsaby:
Maximal width learning of binary functions. Theor. Comput. Sci. 411(1): 138-147 (2010) - [i10]Joel Ratsaby:
Prediction by Compression. CoRR abs/1008.5078 (2010) - [i9]László Kovács, Joel Ratsaby:
Descriptive-complexity based distance for fuzzy sets. CoRR abs/1012.3410 (2010)
2000 – 2009
- 2009
- [i8]Joel Ratsaby:
How random are a learner's mistakes? CoRR abs/0903.3667 (2009) - [i7]Joel Ratsaby:
Combinatorial information distance. CoRR abs/0905.2386 (2009) - [i6]Joel Ratsaby:
Learning, complexity and information density. CoRR abs/0908.4494 (2009) - [i5]Joel Ratsaby:
Random scattering of bits by prediction. CoRR abs/0909.3648 (2009) - 2008
- [j12]Joel Ratsaby:
On the complexity of binary samples. Ann. Math. Artif. Intell. 52(1): 55-65 (2008) - [j11]Joel Ratsaby:
On the complexity of constrained VC-classes. Discret. Appl. Math. 156(6): 903-910 (2008) - [j10]Joel Ratsaby:
Constrained versions of Sauer's lemma. Discret. Appl. Math. 156(14): 2753-2767 (2008) - [j9]Bernard Ycart, Joel Ratsaby:
VC-Dimensions of Random Function Classes. Discret. Math. Theor. Comput. Sci. 10(1) (2008) - [j8]Joel Ratsaby:
An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory. Entropy 10(1): 6-14 (2008) - [r1]Joel Ratsaby:
PAC Learning. Encyclopedia of Algorithms 2008 - [i4]Joel Ratsaby:
Information Width. CoRR abs/0801.4790 (2008) - [i3]Joel Ratsaby:
On the Complexity of Binary Samples. CoRR abs/0801.4794 (2008) - [i2]Joel Ratsaby:
An algorithmic complexity interpretation of Lin's third law of information theory. CoRR abs/0802.4089 (2008) - [i1]Joel Ratsaby, Joël Chaskalovic:
Algorithmic complexity and randomness in elastic solids. CoRR abs/0811.0623 (2008) - 2007
- [j7]Bernard Ycart, Joel Ratsaby:
The VC dimension of k-uniform random hypergraphs. Random Struct. Algorithms 30(4): 564-572 (2007) - [c9]Joel Ratsaby:
Information Efficiency. SOFSEM (1) 2007: 475-487 - 2006
- [j6]Joel Ratsaby:
Complexity of hyperconcepts. Theor. Comput. Sci. 363(1): 2-10 (2006) - [c8]Joel Ratsaby:
On the Combinatorial Representation of Information. COCOON 2006: 479-488 - 2004
- [c7]Joel Ratsaby:
On the Complexity of Samples for Learning. COCOON 2004: 198-209 - 2003
- [j5]Joel Ratsaby:
On learning multicategory classification with sample queries. Inf. Comput. 185(2): 298-327 (2003) - [c6]Joel Ratsaby:
A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation. ALT 2003: 205-220 - 2000
- [c5]Joel Ratsaby, Santosh S. Venkatesh:
On partially blind learning complexity. ISCAS 2000: 765-768
1990 – 1999
- 1999
- [j4]Joel Ratsaby, Vitaly Maiorov:
On the Learnability of Rich Function Classes. J. Comput. Syst. Sci. 58(1): 183-192 (1999) - 1998
- [j3]Vitaly Maiorov, Joel Ratsaby:
The Degree of Approximation of Sets in Euclidean Space Using Sets with Bounded Vapnik-Chervonenkis Dimension. Discret. Appl. Math. 86(1): 81-93 (1998) - [j2]Joel Ratsaby:
Incremental Learning With Sample Queries. IEEE Trans. Pattern Anal. Mach. Intell. 20(8): 883-888 (1998) - 1997
- [j1]Joel Ratsaby, Vitaly Maiorov:
On the Value of Partial Information for Learning from Examples. J. Complex. 13(4): 509-543 (1997) - [c4]Joel Ratsaby, Vitaly Maiorov:
Generalization of the PAC-Model for Learning with Partial Information. EuroCOLT 1997: 51-65 - [c3]Joel Ratsaby:
An Incremental Nearest Neighbor Algorithm with Queries. NIPS 1997: 612-618 - 1996
- [c2]Joel Ratsaby, Ron Meir, Vitaly Maiorov:
Towards Robust Model Selection Using Estimation and Approximation Error Bounds. COLT 1996: 57-67 - 1995
- [c1]Joel Ratsaby, Santosh S. Venkatesh:
Learning from a Mixture of Labeled and Unlabeled Examples with Parametric Side Information. COLT 1995: 412-417
Coauthor Index
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