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Nonparametric Frontier Analysis Using Stata

 Oleg Badunenko , Pavlo Mozharovskyi
The Stata Journal, 2016, 16 (3), pp.550-589. ⟨10.1177/1536867X1601600302⟩
Article dans une revue hal-03189227v1
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Nonparametric imputation by data depth

 Pavlo Mozharovskyi , Julie Josse , François Husson
Journal of the American Statistical Association, 2020, 115 (529), pp.241-253. ⟨10.1080/01621459.2018.1543123⟩
Article dans une revue hal-01440269v1
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Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications

 Morgane Goibert , Stéphan Clémençon , Ekhine Irurozki , Pavlo Mozharovskyi
25th International Conference on Artificial Intelligence and Statistics AISTATS 2022, Mar 2022, Valence, Spain
Communication dans un congrès hal-03537148v1

Exact computation of the halfspace depth

 Rainer Dyckerhoff , Pavlo Mozharovskyi
Computational Statistics and Data Analysis, 2016, 98, pp.19-30. ⟨10.1016/j.csda.2015.12.011⟩
Article dans une revue hal-03188012v1

Functional anomaly detection: a benchmark study

 Guillaume Staerman , Eric Adjakossa , Pavlo Mozharovskyi , Vera Hofer , Jayant Sen Gupta , et al.
International Journal of Data Science and Analytics, 2023, 16 (1), pp.101-117. ⟨10.1007/s41060-022-00366-5⟩
Article dans une revue hal-04268013v1

Depth and depth-based classification with R-package ddalpha

 Oleksii Pokotylo , Pavlo Mozharovskyi , Rainer Dyckerhoff
2016
Pré-publication, Document de travail hal-01355722v1

DDα-classification of asymmetric and fat-tailed data

 Tatjana Lange , Karl Mosler , Pavlo Mozharovskyi
Data Analysis, Machine Learning and Knowledge Discovery, Aug 2012, Hildesheim, Germany
Communication dans un congrès hal-03189251v1
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Functional Isolation Forest

 Guillaume Staerman , Pavlo Mozharovskyi , Stéphan Clémençon , Florence d'Alché-Buc
Proceedings of The Eleventh Asian Conference on Machine Learning, Nov 2019, Nagoya, Japan
Communication dans un congrès hal-02369435v1

Statistical inference for the Russell measure of technical efficiency

 Oleg Badunenko , Pavlo Mozharovskyi
Journal of the Operational Research Society, 2018
Article dans une revue hal-02288042v1

Uniform convergence rates for the approximated halfspace and projection depth

 Stanislav Nagy , Rainer Dyckerhoff , Pavlo Mozharovskyi
Electronic Journal of Statistics , 2020, 14 (2), ⟨10.1214/20-EJS1759⟩
Article dans une revue hal-03189232v1
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Identifying the "Right" Level of Explanation in a Given Situation

 Valérie Beaudouin , Isabelle Bloch , David Bounie , Stéphan Clémençon , Florence d'Alché-Buc , et al.
1st International Workshop on New Foundations for Human-Centered AI (NeHuAI) ECAI 2020, Sep 2020, Santiago de Compostella, Spain. pp.63-66
Communication dans un congrès hal-02507316v1

Fast computation of Tukey trimmed regions and median in dimension p > 2

 Xiaohui Liu , Karl Mosler , Pavlo Mozharovskyi
Journal of Computational and Graphical Statistics, 2019, ⟨10.1080/10618600.2018.1546595⟩
Article dans une revue hal-02288041v1

Fast DD-classification of functional data

 Karl Mosler , Pavlo Mozharovskyi
Statistical Papers, 2017, 58 (4), pp.1055-1089. ⟨10.1007/s00362-015-0738-3⟩
Article dans une revue hal-03189231v1
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Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorization

 Jayneel Parekh , Sanjeel Parekh , Pavlo Mozharovskyi , Gael Richard , Florence d'Alché-Buc
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2024, 32, pp.1392--1405. ⟨10.1109/TASLP.2024.3358049⟩
Article dans une revue hal-04539879v1

Optimized preprocessing and Tiny ML for Attention State Classification

 Yinghao Wang , Rémi Nahon , Enzo Tartaglione , Pavlo Mozharovskyi , Van-Tam Nguyen
2023 IEEE Statistical Signal Processing Workshop (SSP), Jul 2023, Hanoi, Vietnam. pp.695-699, ⟨10.1109/SSP53291.2023.10207930⟩
Communication dans un congrès hal-04254122v1

Depth and Depth-Based Classification with R Package ddalpha

 Oleksii Pokotylo , Pavlo Mozharovskyi , Rainer Dyckerhoff
Journal of Statistical Software, 2019, 91 (5), ⟨10.18637/jss.v091.i05⟩
Article dans une revue hal-03187410v1

The alpha-procedure: a nonparametric invariant method for automatic classification of multi-dimensional objects

 Tatjana Lange , Pavlo Mozharovskyi
Data Analysis, Machine Learning and Knowledge Discovery, Aug 2012, Hildesheim, Germany
Communication dans un congrès hal-03189248v1
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Data depth: computation, applications, and beyond

 Pavlo Mozharovskyi
Statistics [stat]. Institut Polytechnique de Paris, 2022
HDR tel-03780415v1

When OT meets MoM: Robust estimation of Wasserstein Distance

 Guillaume Staerman , Pavlo Mozharovskyi , Florence d'Alché-Buc , Pierre Laforgue
AISTATS 2021, Apr 2021, Virtual Conference, France
Communication dans un congrès hal-03132984v1

Choosing Among Notions of Multivariate Depth Statistics

 Karl Mosler , Pavlo Mozharovskyi
Statistical Science, 2022, 37 (3), ⟨10.1214/21-STS827⟩
Article dans une revue hal-03767631v1

Fast nonparametric classification based on data depth

 Tatjana Lange , Karl Mosler , Pavlo Mozharovskyi
Statistical Papers, 2014, 55 (1), pp.49-69. ⟨10.1007/s00362-012-0488-4⟩
Article dans une revue hal-03178059v1
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Approximate computation of projection depths

 Rainer Dyckerhoff , Pavlo Mozharovskyi , Stanislav Nagy
Computational Statistics and Data Analysis, In press, 157, pp.107166. ⟨10.1016/j.csda.2020.107166⟩
Article dans une revue hal-03189235v1

Depth for Curve Data and Applications

 Pierre Lafaye de Micheaux , Pavlo Mozharovskyi , Myriam Vimond
Journal of the American Statistical Association, In press, pp.1-17. ⟨10.1080/01621459.2020.1745815⟩
Article dans une revue hal-03188029v1

Tukey depth: linear programming and applications

 Pavlo Mozharovskyi
2016
Pré-publication, Document de travail hal-01299491v1

Composite marginal likelihood estimation of spatial autoregressive probit models feasible in very large samples

 Pavlo Mozharovskyi , Jan Vogler
Economics Letters, 2016, 148, pp.87-90. ⟨10.1016/j.econlet.2016.09.022⟩
Article dans une revue hal-03189229v1

A Framework to Learn with Interpretation

 Jayneel Parekh , Pavlo Mozharovskyi , Florence d'Alché-Buc
Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS 2021), Dec 2021, Sydney, Australia
Communication dans un congrès hal-03109686v1

Classifying real-world data with the DDalpha-procedure

 Pavlo Mozharovskyi , Karl Mosler , Tatjana Lange
Advances in Data Analysis and Classification, 2015, 9 (3), pp.287-314. ⟨10.1007/s11634-014-0180-8⟩
Article dans une revue hal-03179752v1
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Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach

 Valérie Beaudouin , Isabelle Bloch , David Bounie , Stéphan Clémençon , Florence d'Alché-Buc , et al.
2020
Pré-publication, Document de travail hal-02506409v1
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The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure

 Guillaume Staerman , Pavlo Mozharovskyi , Stéphan Clémençon
PMLR 108:570-579, 2020
Proceedings/Recueil des communications hal-03132996v1
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Tailoring Mixup to Data using Kernel Warping functions

 Quentin Bouniot , Pavlo Mozharovskyi , Florence d'Alché-Buc
2024
Pré-publication, Document de travail hal-04552478v1
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