Meelis Kull

69 papers A* 5A 6B 1C 2Journal 34Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Enhancing web traffic attacks identification through ensemble methods and feature selection.
Log. J. IGPL
Daniel Urda, Branly Martínez, Nuño Basurto, Meelis Kull, Ángel Arroyo, Álvaro Herrero
2026 J jnl
How Uncertainty Estimation Scales with Sampling in Reasoning Models.
CoRR
Maksym Del, Markus Kängsepp, Marharyta Domnich, Ardi Tampuu, Lisa Yankovskaya, Meelis Kull, Mark Fishel
2025 A conf
Aligning the Evaluation of Probabilistic Predictions with Downstream Value.
ECAI
Novin Shahroudi, Viacheslav Komisarenko, Meelis Kull
2025 J jnl
Aligning the Evaluation of Probabilistic Predictions with Downstream Value.
CoRR
Novin Shahroudi, Viacheslav Komisarenko, Meelis Kull
2025 J jnl
Cost-sensitive classification with cost uncertainty: do we need surrogate losses?
Mach. Learn.
Viacheslav Komisarenko, Meelis Kull
2025 J jnl
Fleet-Wide Model Applicability for Heterogeneous Wind Turbines With Conditional Deep Learning.
IEEE Access
Rasmus Dovnborg Frederiksen, Esben Høg, Meelis Kull, Peter Nielsen
2025 J jnl
On the usefulness of the fit-on-test view on evaluating calibration of classifiers.
Mach. Learn.
Markus Kängsepp, Kaspar Valk, Meelis Kull
2025 A conf
Probability Density from Latent Diffusion Models for Out-of-Distribution Detection.
ECAI
Joonas Järve, Karl Kaspar Haavel, Meelis Kull
2025 J jnl
Probability Density from Latent Diffusion Models for Out-of-Distribution Detection.
CoRR
Joonas Järve, Karl Kaspar Haavel, Meelis Kull
2024 A conf
Cautious Calibration in Binary Classification.
ECAI
Mari-Liis Allikivi, Joonas Järve, Meelis Kull
2024 J jnl
Cautious Calibration in Binary Classification.
CoRR
Mari-Liis Allikivi, Joonas Järve, Meelis Kull
2024 J jnl
Enhancing web traffic attacks identification through ensemble methods and feature selection.
CoRR
Daniel Urda, Branly Martínez, Nuño Basurto, Meelis Kull, Ángel Arroyo, Álvaro Herrero
2024 A* conf
Evaluation of Trajectory Distribution Predictions with Energy Score.
ICML
Novin Shahroudi, Mihkel Lepson, Meelis Kull
2024 A conf
Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness.
ECAI
Viacheslav Komisarenko, Meelis Kull
2024 J jnl
Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness.
CoRR
Viacheslav Komisarenko, Meelis Kull
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part I
ECML/PKDD (1)
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part II
ECML/PKDD (2)
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part III
ECML/PKDD (3)
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IV
ECML/PKDD (4)
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part V
ECML/PKDD (5)
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VI
ECML/PKDD (6)
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII
ECML/PKDD (7)
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024 — ed.
Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VIII
ECML/PKDD (8)
Albert Bifet, Povilas Daniusis, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Kai Puolamäki, Indre Zliobaite
2024 J jnl
Predicting the Activity of Unidentified Chemicals in Complementary Bioassays from the HRMS Data to Pinpoint Potential Endocrine Disruptors.
J. Chem. Inf. Model.
Ida Rahu, Meelis Kull, Anneli Kruve
2023 J jnl
Assuming Locally Equal Calibration Errors for Non-Parametric Multiclass Calibration.
Trans. Mach. Learn. Res.
Kaspar Valk, Meelis Kull
2023 J jnl
Classifier calibration: a survey on how to assess and improve predicted class probabilities.
Mach. Learn.
Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
2023 — conf
Generality-Training of a Classifier for Improved Calibration in Unseen Contexts.
ECML/PKDD (5)
Bhawani Shankar Leelar, Meelis Kull
2022 J jnl
Calibrated Perception Uncertainty Across Objects and Regions in Bird's-Eye-View.
CoRR
Markus Kängsepp, Meelis Kull
2022 J jnl
Ethical and Fairness Implications of Model Multiplicity.
CoRR
Kacper Sokol, Meelis Kull, Jeffrey Chan, Flora Dilys Salim
2022 — conf
Evaluating Classifiers' Performance to Detect Attacks in Website Traffic.
CISIS-ICEUTE
Daniel Urda, Nuño Basurto, Meelis Kull, Álvaro Herrero
2022 J jnl
On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers.
CoRR
Markus Kängsepp, Kaspar Valk, Meelis Kull
2021 J jnl
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories.
IEEE Trans. Knowl. Data Eng.
Fernando Martínez-Plumed, Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana, Peter A. Flach
2021 J jnl
Classifier Calibration: How to assess and improve predicted class probabilities: a survey.
CoRR
Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
2021 C conf
Instance-based Label Smoothing For Better Calibrated Classification Networks.
ICMLA
Mohamed Maher, Meelis Kull
2021 J jnl
Instance-based Label Smoothing For Better Calibrated Classification Networks.
CoRR
Mohamed Maher, Meelis Kull
2021 J jnl
Shift Happens: Adjusting Classifiers.
CoRR
Theodore James Thibault Heiser, Mari-Liis Allikivi, Meelis Kull
2020 J jnl
Correlated daily time series and forecasting in the M4 competition.
CoRR
Anti Ingel, Novin Shahroudi, Markus Kängsepp, Andre Tättar, Viacheslav Komisarenko, Meelis Kull
2019 A* conf
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration.
NeurIPS
Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
2019 J jnl
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration.
CoRR
Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
2019 J jnl
Distribution Calibration for Regression.
CoRR
Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
2019 A* conf
Distribution calibration for regression.
ICML
Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
2019 J jnl
HyperStream: a Workflow Engine for Streaming Data.
CoRR
Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perelló-Nieto, Emma Tonkin, Peter A. Flach
2019 — conf
Non-parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification.
ECML/PKDD (2)
Mari-Liis Allikivi, Meelis Kull
2019 — conf
Shift Happens: Adjusting Classifiers.
ECML/PKDD (2)
Theodore James Thibault Heiser, Mari-Liis Allikivi, Meelis Kull
2018 J jnl
Non-Parametric Calibration of Probabilistic Regression.
CoRR
Hao Song, Meelis Kull, Peter A. Flach
2018 A* conf
Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project.
KDD
Tom Diethe, Mike Holmes, Meelis Kull, Miquel Perelló-Nieto, Kacper Sokol, Hao Song, Emma Tonkin, Niall Twomey, Peter A. Flach
2017 A conf
Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers.
AISTATS
Meelis Kull, Telmo de Menezes e Silva Filho, Peter A. Flach
2017 J jnl
CASP-DM: Context Aware Standard Process for Data Mining.
CoRR
Fernando Martínez-Plumed, Lidia Contreras Ochando, César Ferri, Peter A. Flach, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana
2017 J jnl
Probabilistic Sensor Fusion for Ambient Assisted Living.
CoRR
Tom Diethe, Niall Twomey, Meelis Kull, Peter A. Flach, Ian Craddock
2016 A* conf
Background Check: A General Technique to Build More Reliable and Versatile Classifiers.
ICDM
Miquel Perelló-Nieto, Telmo de Menezes e Silva Filho, Meelis Kull, Peter A. Flach
2016 J jnl
Cost-sensitive boosting algorithms: Do we really need them?
Mach. Learn.
Nikolaos Nikolaou, Narayanan Unny Edakunni, Meelis Kull, Peter A. Flach, Gavin Brown
2016 A conf
Declaratively Capturing Local Label Correlations with Multi-Label Trees.
ECAI
Reem Al-Otaibi, Meelis Kull, Peter A. Flach
2016 J jnl
Reframing in context: A systematic approach for model reuse in machine learning.
AI Commun.
José Hernández-Orallo, Adolfo Martínez Usó, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach, Chowdhury Farhan Ahmed, Nicolas Lachiche
2016 — conf
Subgroup Discovery with Proper Scoring Rules.
ECML/PKDD (2)
Hao Song, Meelis Kull, Peter A. Flach, Georgios Kalogridis
2016 J jnl
The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data.
CoRR
Niall Twomey, Tom Diethe, Meelis Kull, Hao Song, Massimo Camplani, Sion L. Hannuna, Xenofon Fafoutis, Ni Zhu, Pete Woznowski, Peter A. Flach, Ian Craddock
2015 — conf
Model Reuse with Bike rental Station data (Preamble).
DC@PKDD/ECML
Meelis Kull, Nicolas Lachiche, Adolfo Martínez Usó
2015 — conf
Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration.
ECML/PKDD (1)
Meelis Kull, Peter A. Flach
2015 — conf
Precision-Recall-Gain Curves: PR Analysis Done Right.
NIPS
Peter A. Flach, Meelis Kull
2015 — ed.
Proceedings of the ECML/PKDD 2015 Discovery Challenges co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015), Porto, Portugal, September 7-11, 2015.
DC@ECML/PKDD
Adolfo Martínez Usó, João Mendes-Moreira, Luís Moreira-Matias, Meelis Kull, Nicolas Lachiche
2015 B conf
Reframing in Frequent Pattern Mining.
ICTAI
Chowdhury Farhan Ahmed, Md. Samiullah, Nicolas Lachiche, Meelis Kull, Peter A. Flach
2015 — conf
Versatile Decision Trees for Learning Over Multiple Contexts.
ECML/PKDD (1)
Reem Al-Otaibi, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach
2014 C conf
LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion.
ICMLA
Reem Al-Otaibi, Meelis Kull, Peter A. Flach
2014 — conf
Rate-Oriented Point-Wise Confidence Bounds for ROC Curves.
ECML/PKDD (2)
Louise A. C. Millard, Meelis Kull, Peter A. Flach
2014 — conf
Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy.
ECML/PKDD (2)
Meelis Kull, Peter A. Flach
2010 — conf
An Evolutionary Model of DNA Substring Distribution.
Algorithms and Applications
Meelis Kull, Konstantin Tretyakov, Jaak Vilo
2009 J jnl
VisHiC - hierarchical functional enrichment analysis of microarray data.
Nucleic Acids Res.
Darya Krushevskaya, Hedi Peterson, Jüri Reimand, Meelis Kull, Jaak Vilo
2008 J jnl
Fast approximate hierarchical clustering using similarity heuristics.
BioData Min.
Meelis Kull, Jaak Vilo
2007 J jnl
g: Profiler - a web-based toolset for functional profiling of gene lists from large-scale experiments.
Nucleic Acids Res.
Jüri Reimand, Meelis Kull, Hedi Peterson, Jaanus Hansen, Jaak Vilo
2004 J jnl
Expression Profiler: next generation - an online platform for analysis of microarray data.
Nucleic Acids Res.
Misha Kapushesky, Patrick Kemmeren, Aedín C. Culhane, Steffen Durinck, Jan Ihmels, Christine Körner, Meelis Kull, Aurora Torrente, Ugis Sarkans, Jaak Vilo, Alvis Brazma