Pavlo Mozharovskyi

54 papers A* 4A 3C 1Journal 38Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Unified pipeline for generalized mental state detection using EEG signals. Expert Syst. Appl. Yinghao Wang, Rayan Elrawas, Anh-Dung Nguyen, Maxime Girard, Pavlo Mozharovskyi, Enzo Tartaglione, Van-Tam Nguyen
2025	J	`jnl`	Anomaly detection using data depth: multivariate case. Int. J. Data Sci. Anal. Pavlo Mozharovskyi, Romain Valla
2025	J	`jnl`	Data Depth as a Risk. CoRR Arturo Castellanos, Pavlo Mozharovskyi
2025	J	`jnl`	Kernel Trace Distance: Quantum Statistical Metric between Measures through RKHS Density Operators. CoRR Arturo Castellanos, Anna Korba, Pavlo Mozharovskyi, Hicham Janati
2025	J	`jnl`	Memory Constrained Dynamic Subnetwork Update for Transfer Learning. CoRR Aël Quélennec, Pavlo Mozharovskyi, Van-Tam Nguyen, Enzo Tartaglione
2025	J	`jnl`	Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces. CoRR Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela
2025	A*	`conf`	Restyling Unsupervised Concept Based Interpretable Networks with Generative Models. ICLR Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc
2025	J	`jnl`	Self-Supervised Learning of Graph Representations for Network Intrusion Detection. CoRR Lorenzo Guerra, Thomas Chapuis, Guillaume Duc, Pavlo Mozharovskyi, Van-Tam Nguyen
2025	J	`jnl`	Study of Training Dynamics for Memory-Constrained Fine-Tuning. CoRR Aël Quélennec, Nour Hezbri, Pavlo Mozharovskyi, Van-Tam Nguyen, Enzo Tartaglione
2025	A*	`conf`	Tailoring Mixup to Data for Calibration. ICLR Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc
2024	J	`jnl`	A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions. Trans. Mach. Learn. Res. Guillaume Staerman, Pavlo Mozharovskyi, Pierre Colombo, Stéphan Clémençon, Florence d'Alché-Buc
2024	—	`conf`	AI-Driven Intrusion Detection Systems (IDS) on the ROAD Dataset: A Comparative Analysis for Automotive Controller Area Network (CAN). CSCS Lorenzo Guerra, Linhan Xu, Paolo Bellavista, Thomas Chapuis, Guillaume Duc, Pavlo Mozharovskyi, Van-Tam Nguyen
2024	J	`jnl`	AI-Driven Intrusion Detection Systems (IDS) on the ROAD dataset: A Comparative Analysis for automotive Controller Area Network (CAN). CoRR Lorenzo Guerra, Linhan Xu, Pavlo Mozharovskyi, Paolo Bellavista, Thomas Chapuis, Guillaume Duc, Van-Tam Nguyen
2024	J	`jnl`	On Exact Computation of Tukey Depth Central Regions. J. Comput. Graph. Stat. Vít Fojtík, Petra Laketa, Pavlo Mozharovskyi, Stanislav Nagy
2024	J	`jnl`	Restyling Unsupervised Concept Based Interpretable Networks with Generative Models. CoRR Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc
2024	J	`jnl`	Statistical Process Monitoring of Artificial Neural Networks. Technometrics Anna Malinovskaya, Pavlo Mozharovskyi, Philipp Otto
2024	J	`jnl`	Tackling Interpretability in Audio Classification Networks With Non-negative Matrix Factorization. IEEE ACM Trans. Audio Speech Lang. Process. Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Gaël Richard, Florence d'Alché-Buc
2024	—	`conf`	Towards On-Device Learning on the Edge: Ways to Select Neurons to Update Under a Budget Constraint. WACV (Workshops) Aël Quélennec, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
2023	J	`jnl`	Anomaly component analysis. CoRR Romain Valla, Pavlo Mozharovskyi, Florence d'Alché-Buc
2023	J	`jnl`	Fast kernel half-space depth for data with non-convex supports. CoRR Arturo Castellanos, Pavlo Mozharovskyi, Florence d'Alché-Buc, Hicham Janati
2023	J	`jnl`	Functional anomaly detection: a benchmark study. Int. J. Data Sci. Anal. Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
2023	—	`conf`	Optimized preprocessing and Tiny ML for Attention State Classification. SSP Yinghao Wang, Rémi Nahon, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
2023	J	`jnl`	Optimized preprocessing and Tiny ML for Attention State Classification. CoRR Yinghao Wang, Rémi Nahon, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
2023	J	`jnl`	Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorization. CoRR Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Gaël Richard, Florence d'Alché-Buc
2023	J	`jnl`	Tailoring Mixup to Data using Kernel Warping functions. CoRR Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc
2023	J	`jnl`	Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint. CoRR Aël Quélennec, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen
2022	J	`jnl`	Anomaly detection using data depth: multivariate case. CoRR Pavlo Mozharovskyi
2022	—	`book`	Data depth: computation, applications, and beyond. Pavlo Mozharovskyi
2022	J	`jnl`	Functional Anomaly Detection: a Benchmark Study. CoRR Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
2022	A*	`conf`	Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF. NeurIPS Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard
2022	J	`jnl`	Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF. CoRR Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard
2022	A	`conf`	Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. AISTATS Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
2022	J	`jnl`	Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. CoRR Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
2022	J	`jnl`	Statistical monitoring of models based on artificial intelligence. CoRR Anna Malinovskaya, Pavlo Mozharovskyi, Philipp Otto
2021	A*	`conf`	A Framework to Learn with Interpretation. NeurIPS Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc
2021	J	`jnl`	Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
2021	J	`jnl`	Approximate computation of projection depths. Comput. Stat. Data Anal. Rainer Dyckerhoff, Pavlo Mozharovskyi, Stanislav Nagy
2021	J	`jnl`	Depth-based pseudo-metrics between probability distributions. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
2021	A	`conf`	When OT meets MoM: Robust estimation of Wasserstein Distance. AISTATS Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc
2020	J	`jnl`	A Framework to Learn with Interpretation. CoRR Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc
2020	J	`jnl`	Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach. CoRR Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
2020	—	`conf`	Identifying the "right" level of explanation in a given situation. NeHuAI@ECAI Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
2020	J	`jnl`	Statistical inference for the Russell measure of technical efficiency. J. Oper. Res. Soc. Oleg Badunenko, Pavlo Mozharovskyi
2020	A	`conf`	The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measure. AISTATS Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
2020	J	`jnl`	When OT meets MoM: Robust estimation of Wasserstein Distance. CoRR Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc
2019	C	`conf`	Functional Isolation Forest. ACML Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
2019	J	`jnl`	Functional Isolation Forest. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
2019	J	`jnl`	The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
2016	J	`jnl`	Exact computation of the halfspace depth. Comput. Stat. Data Anal. Rainer Dyckerhoff, Pavlo Mozharovskyi
2015	J	`jnl`	Classifying real-world data with the DDα-procedure. Adv. Data Anal. Classif. Pavlo Mozharovskyi, Karl Mosler, Tatjana Lange
2015	—	`—`	Contributions to depth-based classification and computation of the Tukey depth. Pavlo Mozharovskyi
2012	—	`conf`	DD GfKl Tatjana Lange, Karl Mosler, Pavlo Mozharovskyi
2012	J	`jnl`	Fast nonparametric classification based on data depth CoRR Tatjana Lange, Karl Mosler, Pavlo Mozharovskyi
2012	—	`conf`	The Alpha-Procedure: A Nonparametric Invariant Method for Automatic Classification of Multi-Dimensional Objects. GfKl Tatjana Lange, Pavlo Mozharovskyi