Vladimir Pestov

According to our database, Vladimir Pestov authored at least 27 papers between 1999 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Universal consistency of the k-NN rule in metric spaces and Nagata dimension. II.

Sushma Kumari, Vladimir G. Pestov

CoRR, 2023

2022

A universally consistent learning rule with a universally monotone error.

Vladimir Pestov

J. Mach. Learn. Res., 2022

2020

A learning problem whose consistency is equivalent to the non-existence of real-valued measurable cardinals.

Vladimir G. Pestov

CoRR, 2020

Universal consistency of the k-NN rule in metric spaces and Nagata dimension.

Benoit Collins, Sushma Kumari, Vladimir G. Pestov

CoRR, 2020

2019

Elementos da teoria de aprendizagem de máquina supervisionada.

Vladimir G. Pestov

CoRR, 2019

2014

Editorial.

Gonzalo Navarro, Vladimir Pestov

Inf. Syst., 2014

2013

PAC learnability under non-atomic measures: A problem by Vidyasagar.

Vladimir Pestov

Theor. Comput. Sci., 2013

Is the <i>k</i>k-NN classifier in high dimensions affected by the curse of dimensionality?

Vladimir Pestov

Comput. Math. Appl., 2013

Lower Bounds on Performance of Metric Tree Indexing Schemes for Exact Similarity Search in High Dimensions.

Vladimir Pestov

Algorithmica, 2013

PFMFind: A System for Discovery of Peptide Homology and Function.

Aleksandar Stojmirovic, Peter Andreae, Mike Boland, Thomas William Jordan, Vladimir Pestov

Proceedings of the Similarity Search and Applications - 6th International Conference, 2013

Text Categorization via Similarity Search - An Efficient and Effective Novel Algorithm.

Hubert Haoyang Duan, Vladimir Pestov, Varun Singla

Proceedings of the Similarity Search and Applications - 6th International Conference, 2013

2012

Indexability, concentration, and VC theory.

Vladimir Pestov

J. Discrete Algorithms, 2012

2011

PAC learnability versus VC dimension: A footnote to a basic result of statistical learning.

Vladimir Pestov

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010

Intrinsic dimensionality.

Vladimir Pestov

ACM SIGSPATIAL Special, 2010

A Note on Sample Complexity of Learning Binary Output Neural Networks under Fixed Input Distributions.

Vladimir Pestov

Proceedings of the 11th Brazilian Symposium on Neural Networks (SBRN 2010), 2010

Predictive PAC Learnability: A Paradigm for Learning from Exchangeable Input Data.

Vladimir Pestov

Proceedings of the 2010 IEEE International Conference on Granular Computing, 2010

PAC Learnability of a Concept Class under Non-atomic Measures: A Problem by Vidyasagar.

Vladimir Pestov

Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009

Curse of Dimensionality in Pivot Based Indexes.

Ilya Volnyansky, Vladimir Pestov

Proceedings of the Second International Workshop on Similarity Search and Applications, 2009

2008

An axiomatic approach to intrinsic dimension of a dataset.

Vladimir Pestov

Neural Networks, 2008

Hyperlinear and Sofic Groups: A Brief Guide.

Vladimir Pestov

Bull. Symb. Log., 2008

2007

Indexing schemes for similarity search in datasets of short protein fragments.

Aleksandar Stojmirovic, Vladimir Pestov

Inf. Syst., 2007

Intrinsic dimension of a dataset: what properties does one expect?

Vladimir Pestov

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Indexing Schemes for Similarity Search: an Illustrated Paradigm.

Vladimir Pestov, Aleksandar Stojmirovic

Fundam. Informaticae, 2006

Dynamics of Infinite-dimensional Groups - The Ramsey-Dvoretzky-Milman Phenomenon.

Vladimir Pestov

University lecture series 40, American Mathematical Society, ISBN: 978-0-8218-4137-2, 2006

2000

On the geometry of similarity search: Dimensionality curse and concentration of measure.

Vladimir Pestov

Inf. Process. Lett., 2000

1999

Additive models in high dimensions

Markus Hegland, Vladimir Pestov

CoRR, 1999

A Geometric Framework for Modelling Similarity Search.

Vladimir Pestov

Proceedings of the 10th International Workshop on Database & Expert Systems Applications, 1999