Researchers
Tuwe Löfström
Boards, committees etc.
Löfström is an expert in machine learning and knowledge discovery. His basic research interests lie in predicting with confidence and ensemble learning. His applied research is conducted in a variety of domains, in collaboration with partners from both the private and public sector.
Article
Löfström, H., Löfström, T., Johansson, U., Sönströd, C.
(2024).
Calibrated explanations: With uncertainty information and counterfactuals Expert systems with applications, 246.
More information
Pettersson, T., Riveiro, M., Löfström, T.
(2024).
Multimodal fine-grained grocery product recognition using image and OCR text Machine Vision and Applications, 35(4).
More information
Johansson, U., Löfström, T., Boström, H.
(2023).
Conformal Predictive Distribution Trees Annals of Mathematics and Artificial Intelligence.
More information
Löfström, H., Löfström, T., Johansson, U., Sönströd, C.
(2023).
Investigating the impact of calibration on the quality of explanations Annals of Mathematics and Artificial Intelligence.
More information
Johansson, U., Sönströd, C., Löfström, T., Boström, H.
(2022).
Rule extraction with guarantees from regression models Pattern Recognition, 126.
More information
Oucheikh, R., Löfström, T., Ahlberg, E., Carlsson, L.
(2021).
Rolling cargo management using a deep reinforcement learning approach Logistics, 5(1).
More information
Oucheikh, R., Pettersson, T., Löfström, T.
(2021).
Product verification using OCR classification and Mondrian conformal prediction Expert systems with applications, 188.
More information
Johansson, U., Löfström, T., Linusson, H., Boström, H.
(2019).
Efficient Venn Predictors using Random Forests Machine Learning, 108(3), 535-550.
More information
Johansson, U., Linusson, H., Löfström, T., Boström, H.
(2018).
Interpretable regression trees using conformal prediction Expert systems with applications, 97, 394-404.
More information
Löfström, H., Löfström, T., Johansson, U.
(2018).
Interpretable instance-based text classification for social science research projects Archives of Data Science, Series A, 5(1).
More information
Boström, H., Linusson, H., Löfström, T., Johansson, U.
(2017).
Accelerating difficulty estimation for conformal regression forests Annals of Mathematics and Artificial Intelligence, 81(1-2), 125-144.
More information
Löfström, T., Boström, H., Linusson, H., Johansson, U.
(2015).
Bias reduction through conditional conformal prediction Intelligent Data Analysis, 19(6), 1355-1375.
More information
Johansson, U., Boström, H., Löfström, T., Linusson, H.
(2014).
Regression conformal prediction with random forests Machine Learning, 97(1-2), 155-176.
More information
Johansson, U., Sönströd, C., Löfström, T., Boström, H.
(2012).
Obtaining accurate and comprehensible classifiers using oracle coaching Intelligent Data Analysis, Volume 16(Number 2), 247-263.
More information
Book chapter
Johansson, U., König, R., Löfström, T., Sönströd, C., Niklasson, L.
(2009).
Post-processing Evolved Decision Trees.
In:
Ajith Abraham
(Ed.),
Foundations of Computational Intelligence
(pp. 149 -164).
More information
Conference paper
Löfström, H., Löfström, T.
(2024).
Conditional Calibrated Explanations: Finding a Path Between Bias and Uncertainty.
Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024.
More information
Johansson, U., Sönströd, C., Löfström, T., Boström, H.
(2023).
Confidence Classifiers with Guaranteed Accuracy or Precision.
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus.
More information
Löfström, T., Bondaletov, A., Ryasik, A., Boström, H., Johansson, U.
(2023).
Tutorial on using Conformal Predictive Systems in KNIME.
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus.
More information
Uddin, N., Löfström, T.
(2023).
Applications of Conformal Regression on Real-world Industrial Use Cases using Crepes and MAPIE.
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus.
More information
Johansson, U., Löfström, T., Sönströd, C., Löfström, H.
(2023).
Conformal Prediction for Accuracy Guarantees in Classification with Reject Option.
International Conference on Modeling Decisions for Artificial Intelligence Umeå, Sweden 19 June 2023.
More information
Pettersson, T., Riveiro, M., Löfström, T.
(2023).
Explainable local and global models for fine-grained multimodal product recognition.
Multimodal KDD 2023, International Workshop on Multimodal Learning, in conjunction with 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), August 6–10, 2023, Long Beach, CA, USA.
More information
Pettersson, T., Oucheikh, R., Löfström, T.
(2022).
NLP Cross-Domain Recognition of Retail Products.
New York:
Association for Computing Machinery (ACM), ICMLT 2022: 7th International Conference on Machine Learning Technologies (ICMLT), Virtual Conference, 11-13 March 2022.
More information
Johansson, U., Löfström, T., Ståhl, N.
(2022).
Well-Calibrated Rule Extractors.
11th Symposium on Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK.
More information
Löfström, T., Ryasik, A., Johansson, U.
(2022).
Tutorial for using conformal prediction in KNIME.
11th Symposium on Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK.
More information
Johansson, U., Löfström, T., Boström, H.
(2021).
Well-Calibrated and Sharp Interpretable Multi-Class Models.
18th International Conference, MDAI 2021, Umeå, Sweden, September 27–30, 2021, Proceedings.
More information
Johansson, U., Löfström, T., Boström, H.
(2021).
Calibrating multi-class models.
Conformal and Probabilistic Prediction and Applications, 8-10 September 2021, Virtual.
More information
Boström, H., Johansson, U., Löfström, T.
(2021).
Mondrian conformal predictive distributions.
Conformal and Probabilistic Prediction and Applications, 8-10 September 2021, Virtual.
More information
Johansson, U., Bostrom, H., Löfström, T.
(2021).
Investigating Normalized Conformal Regressors.
2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021, 5 December 2021 through 7 December 2021.
More information
Johansson, U., Löfström, T.
(2020).
Well-calibrated and specialized probability estimation trees.
2020 SIAM International Conference on Data Mining, SDM 2020, 7 May 2020 through 9 May 2020.
More information
Johansson, U., Sonstrod, C., Löfström, T., Bostrom, H.
(2019).
Customized interpretable conformal regressors.
6th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019, Washington, United States, 5 - 8 October, 2019.
More information
Johansson, U., Löfström, T., Boström, H.
(2019).
Calibrating probability estimation trees using Venn-Abers predictors.
19th SIAM International Conference on Data Mining, SDM 2019, Hyatt Regency Calgary, Calgary, Canada, 2 - 4 May 2019.
More information
Johansson, U., Löfström, T., Boström, H., Sönströd, C.
(2019).
Interpretable and Specialized Conformal Predictors.
Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications, 9-11 September 2019, Golden Sands, Bulgaria.
More information
Giri, C., Johansson, U., Löfström, T.
(2019).
Predictive modeling of campaigns to quantify performance in fashion retail industry.
2019 IEEE International Conference on Big Data, Big Data 2019, Los Angeles, United States, 9-12 December 2019.
More information
Linusson, H., Johansson, U., Boström, H., Löfström, T.
(2018).
Classification with reject option using conformal prediction.
22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018; Melbourne; Australia; 3 June 2018 through 6 June 2018.
More information
Sundell, H., Löfström, T., Johansson, U.
(2018).
Explorative multi-objective optimization of marketing campaigns for the fashion retail industry.
13th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS), Belfast, Ireland, 21-24 August, 2018.
More information
Johansson, U., Löfström, T., Sundell, H.
(2018).
Venn predictors using lazy learners.
The 2018 World Congress in Computer Science, Computer Engineering & Applied Computing, July 30 - August 02, Las Vegas, Nevada, USA.
More information
Johansson, U., Löfström, T., Sundell, H., Linusson, H., Gidenstam, A., Boström, H.
(2018).
Venn predictors for well-calibrated probability estimation trees.
Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications, 11-13 June 2018.
More information
Löfström, T., Johansson, U., Balkow, J., Sundell, H.
(2018).
A data-driven approach to online fitting services.
13th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS), Belfast, Ireland, 21-24 August, 2018.
More information
Johansson, U., Linusson, H., Löfström, T., Boström, H.
(2017).
Model-agnostic nonconformity functions for conformal classification.
2017 International Joint Conference on Neural Networks, IJCNN 2017, 14 May 2017 through 19 May 2017.
More information
Linusson, H., Norinder, U., Boström, H., Johansson, U., Löfström, T.
(2017).
On the calibration of aggregated conformal predictors.
The 6th Symposium on Conformal and Probabilistic Prediction with Applications, (COPA 2017), 13-16 June, 2017, Stockholm, Sweden.
More information
Ahlberg, E.
Winiwarter, S.
Boström, H.
Linusson, H.
Löfström, T.
Norinder, U.
, ... Carlsson L.
(2017).
Using conformal prediction to prioritize compound synthesis in drug discovery.
The 6th Symposium on Conformal and Probabilistic Prediction with Applications, (COPA 2017), 13-16 June, 2017, Stockholm, Sweden.
More information
Boström, H., Linusson, H., Löfström, T., Johansson, U.
(2016).
Evaluation of a variance-based nonconformity measure for regression forests.
5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016; Madrid; Spain; 20 April 2016 through 22 April 2016.
More information
Linusson, H., Johansson, U., Boström, H., Löfström, T.
(2016).
Reliable Confidence Predictions Using Conformal Prediction.
PAKDD 2016: Advances in Knowledge Discovery and Data Mining, Auckland, April 19-22, 2016.
More information
Radon, A.
Johansson, P.
Sundström, M.
Alm, H.
Behre, M.
Göbel, H.
, ... Wallström S.
(2016).
What happens when retail meets research?: Special session.
ANZMAC Conference 2016 - Marketing in a Post-Disciplinary Era, Christchurch, 5-7 December, 2016.
More information
Löfström, T., Zhao, J., Linnusson, H., Jansson, K.
(2015).
Predicting Adverse Drug Events with Confidence.
Thirteenth Scandinavian Conference on Artificial Intelligence.
More information
Linusson, H., Johansson, U., Boström, H., Löfström, T.
(2014).
Efficiency Comparison of Unstable Transductive and Inductive Conformal Classifiers.
Artificial Intelligence Applications and Innovations.
More information
Johansson, U., König, R., Linusson, H., Löfström, T., Boström, H.
(2014).
Rule Extraction with Guaranteed Fidelity.
Artificial Intelligence Applications and Innovations.
More information
Linusson, H., Johansson, U., Löfström, T.
(2014).
Signed-Error Conformal Regression.
18th Pacific-Asia Conference, PAKDD 2014 Tainan, Taiwan, May 13-16, 2014.
More information
Johansson, U., Boström, H., Löfström, T.
(2013).
Conformal Prediction Using Decision Trees.
IEEE International Conference on Data Mining.
More information
Johansson, U., Löfström, T., Boström, H.
(2013).
Overproduce-and-Select: The Grim Reality.
IEEE Symposium on Computational Intelligence and Ensemble Learning (CIEL), 16-19 April 2013 , Singapore.
More information
Johansson, U., König, R., Löfström, T., Boström, H.
(2013).
Evolved Decision Trees as Conformal Predictors.
IEEE Congress on Evolutionary Computation, 20-23 June 2013.
More information
Löfström, T., Johansson, U., Boström, H.
(2013).
Effective Utilization of Data in Inductive Conformal Prediction using Ensembles of Neural Networks.
International Joint Conference on Neural Networks, Dallas, TX, USA, August 4-9, 2013..
More information
Johansson, U., Löfström, T., Boström, H.
(2013).
Random Brains.
International Joint Conference on Neural Networks, Dallas, TX, USA, August 4-9, 2013..
More information
Johansson, U., Löfström, T.
(2012).
Producing Implicit Diversity in ANN Ensembles.
Neural Networks (IJCNN), The 2012 International Joint Conference on.
More information
Johansson, U., Sönströd, C., Löfström, T.
(2011).
One Tree to Explain Them All.
IEEE Congress on Evolutionary Computation (CEC).
More information
Johansson, U., Löfström, T., Sönströd, C.
(2011).
Locally Induced Predictive Models.
IEEE International Conference on Systems, Man, and Cybernetics.
More information
Johansson, U., König, R., Löfström, T., Niklasson, L.
(2010).
Using Imaginary Ensembles to Select GP Classifiers.
13th European Conference, EuroGP 2010, Istanbul, Turkey, April 7-9, 2010.
More information
Johansson, U., Sönströd, C., Norinder, U., Boström, H., Löfström, T.
(2010).
Using Feature Selection with Bagging and Rule Extraction in Drug Discovery.
Advances in Intelligent Decision Technologies, Second KES International Symposium IDT 2010.
More information
König, R., Johansson, U., Löfström, T., Niklasson, L.
(2010).
Improving GP Classification Performance by Injection of Decision Trees.
WCCI 2010 IEEE World Congress on Computational Intelligence, CEC 2010.
More information
Johansson, U., Sönströd, C., Löfström, T.
(2010).
Oracle Coached Decision Trees and Lists.
Advances in Intelligent Data Analysis IX, 9th International Symposium, IDA 2010.
More information
Löfström, T., Johansson, U., Boström, H.
(2010).
Comparing Methods for Generating Diverse Ensembles of Artificial Neural Networks.
WCCI 2010 IEEE World Congress on Computational Intelligence, IJCNN 2010.
More information
Johansson, U., Sönströd, C., Löfström, T., König, R.
(2009).
Using Genetic Programming to Obtain Implicit Diversity.
2009 IEEE Congress on Evolutionary Computation (CEC 2009), Trondheim, Norge.
More information
Löfström, T., Johansson, U., Borström, H.
(2009).
Ensemble Member Selection Using Multi-Objective Optimization.
2009 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING, Nashville, TN, USA.
More information
Sönströd, C., Johansson, U., Löfström, T.
(2009).
Evaluating Algorithms for Concept Description.
5th International Conference on Data Mining - DMIN 09, Las Vegas, USA.
More information
Löfström, T., Johansson, U., Boström, H.
(2009).
Using Optimized Optimization Criteria in Ensemble Member Selection.
SWIFT 2008 - Skövde Workshop on Information Fusion Topics.
More information
Löfström, T., Johansson, U., Boström, H.
(2008).
On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers.
Seventh International Conference on Machine Learning and Applications.
More information
Löfström, T., Johansson, U., Boström, H.
(2008).
The Problem with Ranking Ensembles Based on Training or Validation Performance.
IJCNN 2008, Hong Kong, June 1- 6, 2008.
More information
Johansson, U., König, R., Löfström, T., Niklasson, L.
(2008).
Increasing Rule Extraction Accuracy by Post-processing GP Trees.
CEC 2008, Hong Kong, June 1-6, 2008.
More information
Johansson, U., Sönströd, C., Boström, H., Löfström, T.
(2008).
Chipper: A Novel Algorithm for Concept Description.
Paper presented at the 10th Scandinavian Conference on Artificial Intelligence SCAI 2008.
More information
Johansson, U., Löfström, T., Niklasson, L.
(2008).
Evaluating Standard Techniques for Implicit Diversity.
Pacific-Asia Conference on Knowledge Discovery and Data Mining.
More information
Johansson, U., Löfström, T., Niklasson, L.
(2007).
Empirically Investigating the Importance of Diversity.
International Conference on Information Fusion.
More information
Johansson, U., Löfström, T., Niklasson, L.
(2007).
The Importance of Diversity in Neural Network Ensembles: An Empirical Investigation.
The International Joint Conference on Neural Networks.
More information
Report
Löfström, T., Ralsmark, H., Johansson, U.
(2021).
Collusion in algorithmic pricing.
Stockholm:
Konkurrensverket
More information
Löfström, T., Linnusson, H., Sönströd, C., Johansson, U.
(2015).
System Health Monitoring using Conformal Anomaly Detection.
Borås:
Högskolan i Borås
More information