Kull, Meelis

18 publications

MLJ 2025 Cost-Sensitive Classification with Cost Uncertainty: Do We Need Surrogate Losses? Viacheslav Komisarenko, Meelis Kull

MLJ 2025 On the Usefulness of the Fit-on-Test View on Evaluating Calibration of Classifiers Markus Kängsepp, Kaspar Valk, Meelis Kull

ICML 2024 Evaluation of Trajectory Distribution Predictions with Energy Score Novin Shahroudi, Mihkel Lepson, Meelis Kull

TMLR 2023 Assuming Locally Equal Calibration Errors for Non-Parametric Multiclass Calibration Kaspar Valk, Meelis Kull

MLJ 2023 Classifier Calibration: A Survey on How to Assess and Improve Predicted Class Probabilities Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach

ECML-PKDD 2023 Generality-Training of a Classifier for Improved Calibration in Unseen Contexts Bhawani Shankar Leelar, Meelis Kull

NeurIPS 2019 Beyond Temperature Scaling: Obtaining Well-Calibrated Multi-Class Probabilities with Dirichlet Calibration Meelis Kull, Miquel Perello Nieto, Markus Kängsepp, Telmo Silva Filho, Hao Song, Peter Flach

ICML 2019 Distribution Calibration for Regression Hao Song, Tom Diethe, Meelis Kull, Peter Flach

ECML-PKDD 2019 Non-Parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification Mari-Liis Allikivi, Meelis Kull

ECML-PKDD 2019 Shift Happens: Adjusting Classifiers Theodore James Thibault Heiser, Mari-Liis Allikivi, Meelis Kull

AISTATS 2017 Beta Calibration: A Well-Founded and Easily Implemented Improvement on Logistic Calibration for Binary Classifiers Meelis Kull, Telmo de Menezes e Silva Filho, Peter A. Flach

MLJ 2016 Cost-Sensitive Boosting Algorithms: Do We Really Need Them? Nikolaos Nikolaou, Narayanan Unny Edakunni, Meelis Kull, Peter A. Flach, Gavin Brown

ECML-PKDD 2016 Subgroup Discovery with Proper Scoring Rules Hao Song, Meelis Kull, Peter A. Flach, Georgios Kalogridis

ECML-PKDD 2015 Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration Meelis Kull, Peter A. Flach

NeurIPS 2015 Precision-Recall-Gain Curves: PR Analysis Done Right Peter Flach, Meelis Kull

ECML-PKDD 2015 Versatile Decision Trees for Learning over Multiple Contexts Reem Al-Otaibi, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach

ECML-PKDD 2014 Rate-Oriented Point-Wise Confidence Bounds for ROC Curves Louise A. C. Millard, Meelis Kull, Peter A. Flach

ECML-PKDD 2014 Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy Meelis Kull, Peter A. Flach