Pavlo Mozharovskyi

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 36

Top Venues

CoRR

AISTATS

Comput. Stat. Data Anal.

NeurIPS

University of Cologne (PHD)

Education History

University of Cologne

PHD

Publications

Aël Quélennec, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
Towards On-Device Learning on the Edge: Ways to Select Neurons to Update Under a Budget Constraint. WACV (Workshops) (2024)
Anna Malinovskaya, Pavlo Mozharovskyi, Philipp Otto
Statistical Process Monitoring of Artificial Neural Networks. Technometrics 66 (1) (2024)
Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models. CoRR (2024)
Vít Fojtík, Petra Laketa, Pavlo Mozharovskyi, Stanislav Nagy
On Exact Computation of Tukey Depth Central Regions. J. Comput. Graph. Stat. 33 (2) (2024)
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Gaël Richard, Florence d'Alché-Buc
Tackling Interpretability in Audio Classification Networks With Non-negative Matrix Factorization. IEEE ACM Trans. Audio Speech Lang. Process. 32 (2024)
Guillaume Staerman, Pavlo Mozharovskyi, Pierre Colombo, Stéphan Clémençon, Florence d'Alché-Buc
A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions. Trans. Mach. Learn. Res. 2024 (2024)
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Gaël Richard, Florence d'Alché-Buc
Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorization. CoRR (2023)
Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
Functional anomaly detection: a benchmark study. Int. J. Data Sci. Anal. 16 (1) (2023)
Yinghao Wang, Rémi Nahon, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
Optimized preprocessing and Tiny ML for Attention State Classification. CoRR (2023)
Yinghao Wang, Rémi Nahon, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
Optimized preprocessing and Tiny ML for Attention State Classification. SSP (2023)
Arturo Castellanos, Pavlo Mozharovskyi, Florence d'Alché-Buc, Hicham Janati
Fast kernel half-space depth for data with non-convex supports. CoRR (2023)
Romain Valla, Pavlo Mozharovskyi, Florence d'Alché-Buc
Anomaly component analysis. CoRR (2023)
Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc
Tailoring Mixup to Data using Kernel Warping functions. CoRR (2023)
Aël Quélennec, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint. CoRR (2023)
Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
Functional Anomaly Detection: a Benchmark Study. CoRR (2022)
Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. CoRR (2022)
Pavlo Mozharovskyi
Anomaly detection using data depth: multivariate case. CoRR (2022)
Anna Malinovskaya, Pavlo Mozharovskyi, Philipp Otto
Statistical monitoring of models based on artificial intelligence. CoRR (2022)
Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. AISTATS (2022)
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF. NeurIPS (2022)
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF. CoRR (2022)
Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc
When OT meets MoM: Robust estimation of Wasserstein Distance. AISTATS (2021)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
Depth-based pseudo-metrics between probability distributions. CoRR (2021)
Rainer Dyckerhoff, Pavlo Mozharovskyi, Stanislav Nagy
Approximate computation of projection depths. Comput. Stat. Data Anal. 157 (2021)
Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc
A Framework to Learn with Interpretation. NeurIPS (2021)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis. CoRR (2021)
Oleg Badunenko, Pavlo Mozharovskyi
Statistical inference for the Russell measure of technical efficiency. J. Oper. Res. Soc. 71 (3) (2020)
Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc
When OT meets MoM: Robust estimation of Wasserstein Distance. CoRR (2020)
Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
Identifying the "right" level of explanation in a given situation. NeHuAI@ECAI (2020)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measure. AISTATS (2020)
Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach. CoRR (2020)
Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc
A Framework to Learn with Interpretation. CoRR (2020)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure. CoRR (2019)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
Functional Isolation Forest. ACML (2019)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
Functional Isolation Forest. CoRR (2019)
Rainer Dyckerhoff, Pavlo Mozharovskyi
Exact computation of the halfspace depth. Comput. Stat. Data Anal. 98 (2016)
Pavlo Mozharovskyi, Karl Mosler, Tatjana Lange
Classifying real-world data with the DDα-procedure. Adv. Data Anal. Classif. 9 (3) (2015)
Tatjana Lange, Pavlo Mozharovskyi
The Alpha-Procedure: A Nonparametric Invariant Method for Automatic Classification of Multi-Dimensional Objects. GfKl (2012)
Tatjana Lange, Karl Mosler, Pavlo Mozharovskyi
-Classification of Asymmetric and Fat-Tailed Data. GfKl (2012)
Tatjana Lange, Karl Mosler, Pavlo Mozharovskyi
Fast nonparametric classification based on data depth CoRR (2012)

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Publication Activity (10 Years)

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Pavlo Mozharovskyi