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Pavlo Mozharovskyi
Pavlo Mozharovskyi
LTCI, Telecom Paris, Institut Polytechnique de Paris
Verified email at telecom-paris.fr - Homepage
Title
Cited by
Cited by
Year
Fast nonparametric classification based on data depth
T Lange, K Mosler, P Mozharovskyi
Statistical Papers 55, 49-69, 2014
1302014
Nonparametric frontier analysis using Stata
O Badunenko, P Mozharovskyi
The Stata Journal 16 (3), 550-589, 2016
1002016
Exact computation of the halfspace depth
R Dyckerhoff, P Mozharovskyi
Computational Statistics & Data Analysis 98, 19-30, 2016
862016
Flexible and context-specific AI explainability: a multidisciplinary approach
V Beaudouin, I Bloch, D Bounie, S Clémençon, F d'Alché-Buc, J Eagan, ...
arXiv preprint arXiv:2003.07703, 2020
782020
Depth and depth-based classification with R-package ddalpha
O Pokotylo, P Mozharovskyi, R Dyckerhoff
arXiv preprint arXiv:1608.04109, 2016
732016
Functional isolation forest
G Staerman, P Mozharovskyi, S Clémençon, F d’Alché-Buc
Asian Conference on Machine Learning, 332-347, 2019
642019
Choosing among notions of multivariate depth statistics
K Mosler, P Mozharovskyi
Statistical Science 37 (3), 348-368, 2022
482022
Fast DD-classification of functional data
K Mosler, P Mozharovskyi
Statistical Papers 58, 1055-1089, 2017
452017
Youthful and age‐related matreotypes predict drugs promoting longevity
C Statzer, E Jongsma, SX Liu, A Dakhovnik, F Wandrey, P Mozharovskyi, ...
Aging Cell 20 (9), e13441, 2021
372021
Fast Computation of Tukey Trimmed Regions and Median in Dimension p > 2
X Liu, K Mosler, P Mozharovskyi
Journal of Computational and Graphical Statistics 28 (3), 682-697, 2019
372019
A framework to learn with interpretation
J Parekh, P Mozharovskyi, F d'Alché-Buc
Advances in Neural Information Processing Systems 34, 24273-24285, 2021
322021
When ot meets mom: Robust estimation of wasserstein distance
G Staerman, P Laforgue, P Mozharovskyi, F d’Alché-Buc
International Conference on Artificial Intelligence and Statistics, 136-144, 2021
292021
A pseudo-metric between probability distributions based on depth-trimmed regions
G Staerman, P Mozharovskyi, P Colombo, S Clémençon, F d'Alché-Buc
arXiv preprint arXiv:2103.12711, 2021
28*2021
Classifying real-world data with the -procedure
P Mozharovskyi, K Mosler, T Lange
Advances in Data Analysis and Classification 9, 287-314, 2015
282015
The area of the convex hull of sampled curves: a robust functional statistical depth measure
G Staerman, P Mozharovskyi, S Clémen
International Conference on Artificial Intelligence and Statistics, 570-579, 2020
252020
Depth for curve data and applications
PL De Micheaux, P Mozharovskyi, M Vimond
Journal of the American Statistical Association 116 (536), 1881-1897, 2021
212021
Approximate computation of projection depths
R Dyckerhoff, P Mozharovskyi, S Nagy
Computational statistics & data analysis 157, 107166, 2021
202021
Uniform convergence rates for the approximated halfspace and projection depth
S Nagy, R Dyckerhoff, P Mozharovskyi
192020
DDα-Classification of Asymmetric and Fat-Tailed Data
T Lange, K Mosler, P Mozharovskyi
Data analysis, machine learning and knowledge discovery, 71-78, 2014
192014
Nonparametric imputation by data depth
P Mozharovskyi, J Josse, F Husson
Journal of the American Statistical Association, 2019
182019
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