Meelis Kull

Orcid: 0000-0001-9257-595X

According to our database1, Meelis Kull authored at least 45 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Predicting the Activity of Unidentified Chemicals in Complementary Bioassays from the HRMS Data to Pinpoint Potential Endocrine Disruptors.
J. Chem. Inf. Model., 2024

Evaluation of Trajectory Distribution Predictions with Energy Score.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Cautious Calibration in Binary Classification.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
Classifier calibration: a survey on how to assess and improve predicted class probabilities.
Mach. Learn., September, 2023

Assuming Locally Equal Calibration Errors for Non-Parametric Multiclass Calibration.
Trans. Mach. Learn. Res., 2023

Generality-Training of a Classifier for Improved Calibration in Unseen Contexts.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

2022
Calibrated Perception Uncertainty Across Objects and Regions in Bird's-Eye-View.
CoRR, 2022

On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers.
CoRR, 2022

Ethical and Fairness Implications of Model Multiplicity.
CoRR, 2022

Evaluating Classifiers' Performance to Detect Attacks in Website Traffic.
Proceedings of the International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022), 2022

2021
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories.
IEEE Trans. Knowl. Data Eng., 2021

Classifier Calibration: How to assess and improve predicted class probabilities: a survey.
CoRR, 2021

Instance-based Label Smoothing For Better Calibrated Classification Networks.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2020
Correlated daily time series and forecasting in the M4 competition.
CoRR, 2020

2019
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration.
CoRR, 2019

HyperStream: a Workflow Engine for Streaming Data.
CoRR, 2019

Shift Happens: Adjusting Classifiers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Non-parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Distribution calibration for regression.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Non-Parametric Calibration of Probabilistic Regression.
CoRR, 2018

Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017
CASP-DM: Context Aware Standard Process for Data Mining.
CoRR, 2017

Probabilistic Sensor Fusion for Ambient Assisted Living.
CoRR, 2017

Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Cost-sensitive boosting algorithms: Do we really need them?
Mach. Learn., 2016

The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data.
CoRR, 2016

Reframing in context: A systematic approach for model reuse in machine learning.
AI Commun., 2016

Subgroup Discovery with Proper Scoring Rules.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Background Check: A General Technique to Build More Reliable and Versatile Classifiers.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Declaratively Capturing Local Label Correlations with Multi-Label Trees.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
Model Reuse with Bike rental Station data (Preamble).
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), 2015

Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Versatile Decision Trees for Learning Over Multiple Contexts.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Precision-Recall-Gain Curves: PR Analysis Done Right.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Reframing in Frequent Pattern Mining.
Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

2014
Rate-Oriented Point-Wise Confidence Bounds for ROC Curves.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

2010
An Evolutionary Model of DNA Substring Distribution.
Proceedings of the Algorithms and Applications, 2010

2009
VisHiC - hierarchical functional enrichment analysis of microarray data.
Nucleic Acids Res., 2009

2008
Fast approximate hierarchical clustering using similarity heuristics.
BioData Min., 2008

2007
g: Profiler - a web-based toolset for functional profiling of gene lists from large-scale experiments.
Nucleic Acids Res., 2007

2004
Expression Profiler: next generation - an online platform for analysis of microarray data.
Nucleic Acids Res., 2004


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