Tony Lindgren

According to our database, Tony Lindgren authored at least 36 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Ijuice: integer JUstIfied counterfactual explanations.

Alejandro Kuratomi, Ioanna Miliou, Zed Lee, Tony Lindgren, Panagiotis Papapetrou

Mach. Learn., July, 2024

Automotive fault nowcasting with machine learning and natural language processing.

John Pavlopoulos, Alv Romell, Jacob Curman, Olof Steinert, Tony Lindgren, Markus Borg, Korbinian Randl

Mach. Learn., February, 2024

Z-Time: efficient and effective interpretable multivariate time series classification.

Zed Lee, Tony Lindgren, Panagiotis Papapetrou

Data Min. Knowl. Discov., January, 2024

A Strategy Fusion-Based Multiobjective Optimization Approach for Agile Earth Observation Satellite Scheduling Problem.

He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Ran Wang, Yanjie Song

IEEE Trans. Geosci. Remote. Sens., 2024

Evaluating the Reliability of Self-Explanations in Large Language Models.

Korbinian Randl, John Pavlopoulos, Aron Henriksson, Tony Lindgren

CoRR, 2024

A Cost-Sensitive Transformer Model for Prognostics Under Highly Imbalanced Industrial Data.

Ali Beikmohammadi, Mohammad Hosein Hamian, Neda Khoeyniha, Tony Lindgren, Olof Steinert, Sindri Magnússon

CoRR, 2024

SCANIA Component X Dataset: A Real-World Multivariate Time Series Dataset for Predictive Maintenance.

Zahra Kharazian, Tony Lindgren, Sindri Magnússon, Olof Steinert, Oskar Andersson Reyna

CoRR, 2024

SHAP-Driven Explainability in Survival Analysis for Predictive Maintenance Applications.

Monireh Kargar, Zahra Kharazian, Ioanna Miliou, Tony Lindgren

Proceedings of Workshop on Embracing Human-Aware AI in Industry 5.0 (HAII5.0 2024) co-located with the 27th European Conference on Artificial Intelligence (ECAI 2024), 2024

CICLe: Conformal In-Context Learning for Largescale Multi-Class Food Risk Classification.

Korbinian Randl, John Pavlopoulos, Aron Henriksson, Tony Lindgren

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Weibull recurrent neural networks for failure prognosis using histogram data.

Maharshi Harshadbhai Dhada, Ajith Kumar Parlikad, Olof Steinert, Tony Lindgren

Neural Comput. Appl., February, 2023

Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning.

Lawrence A. Bull, Domenic Di Francesco, Maharshi Harshadbhai Dhada, Olof Steinert, Tony Lindgren, Ajith Kumar Parlikad, Andrew B. Duncan, Mark Girolami

Comput. Aided Civ. Infrastructure Eng., 2023

AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, a Framework Based on Active Learning and Transfer Learning.

Zahra Kharazian, Mahmoud Rahat, Fábio F. Gama, Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk, Tony Lindgren, Sindri Magnússon

Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics.

Kaiji Sun, Sindri Magnússon, Olof Steinert, Tony Lindgren

Proceedings of the IEEE International Conference on Prognostics and Health Management, 2023

ORANGE: Opposite-label soRting for tANGent Explanations in heterogeneous spaces.

Alejandro Kuratomi, Zed Lee, Ioanna Miliou, Tony Lindgren, Panagiotis Papapetrou

Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

2022

Automotive Multilingual Fault Diagnosis.

John Pavlopoulos, Alv Romell, Jacob Curman, Olof Steinert, Tony Lindgren, Markus Borg

CoRR, 2022

Knowledge Transfer in Engineering Fleets: Hierarchical Bayesian Modelling for Multi-Task Learning.

Lawrence A. Bull, Maharshi Harshadbhai Dhada, Olof Steinert, Tony Lindgren, Ajith Kumar Parlikad, Andrew B. Duncan, Mark Girolami

CoRR, 2022

Measuring the Burden of (Un)fairness Using Counterfactuals.

Alejandro Kuratomi, Evaggelia Pitoura, Panagiotis Papapetrou, Tony Lindgren, Panayiotis Tsaparas

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

Low dimensional synthetic data generation for improving data driven prognostic models.

Tony Lindgren, Olof Steinert

Proceedings of the 2022 IEEE International Conference on Prognostics and Health Management, 2022

JUICE: JUstIfied Counterfactual Explanations.

Alejandro Kuratomi, Ioanna Miliou, Zed Lee, Tony Lindgren, Panagiotis Papapetrou

Proceedings of the Discovery Science - 25th International Conference, 2022

2021

Z-Hist: A Temporal Abstraction of Multivariate Histogram Snapshots.

Zed Lee, Nicholas Anton, Panagiotis Papapetrou, Tony Lindgren

Proceedings of the Advances in Intelligent Data Analysis XIX, 2021

Hybrid feature tweaking: Combining random forest similarity tweaking with CLPFD.

Tony Mattias Lindgren

Proceedings of the ICCDE 2021: 7th International Conference on Computing and Data Engineering, Phuket, Thailand, January 15, 2021

2020

Prediction of Global Navigation Satellite System Positioning Errors with Guarantees.

Alejandro Kuratomi, Tony Lindgren, Panagiotis Papapetrou

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

Z-Miner: An Efficient Method for Mining Frequent Arrangements of Event Intervals.

Zed Lee, Tony Lindgren, Panagiotis Papapetrou

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Evaluation of Dimensionality Reduction Techniques-Principal Feature Analysis in case of Text Classification Problems.

Michael Mammo, Tony Lindgren

Proceedings of the ICCDE 2020: The 6th International Conference on Computing and Data Engineering, 2020

2019

A Methodology for Prognostics Under the Conditions of Limited Failure Data Availability.

Gishan Don Ranasinghe, Tony Lindgren, Mark Girolami, Ajith Kumar Parlikad

IEEE Access, 2019

Example-Based Feature Tweaking Using Random Forests.

Tony Lindgren, Panagiotis Papapetrou, Isak Samsten, Lars Asker

Proceedings of the 20th IEEE International Conference on Information Reuse and Integration for Data Science, 2019

2018

On Data Driven Organizations and the Necessity of Interpretable Models.

Tony Lindgren

Proceedings of the Smart Grid and Internet of Things - Second EAI International Conference, 2018

2017

Conformal Prediction Using Random Survival Forests.

Henrik Boström, Lars Asker, Ram B. Gurung, Isak Karlsson, Tony Lindgren, Panagiotis Papapetrou

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

Randomized Separate and Conquer Rule induction.

Tony Lindgren

Proceedings of the International Conference on Compute and Data Analysis, 2017

2016

Learning Decision Trees from Histogram Data Using Multiple Subsets of Bins.

Ram B. Gurung, Tony Lindgren, Henrik Boström

Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

2012

Troubleshooting ECU Programmed by Bodybuilders.

Tony Lindgren

Proceedings of the 2012 International Conference on Connected Vehicles and Expo, 2012

2006

On handling conflicts between rules with numerical features.

Tony Lindgren

Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

2004

Resolving rule conflicts with double induction.

Tony Lindgren, Henrik Boström

Intell. Data Anal., 2004

Methods for Rule Conflict Resolution.

Tony Lindgren

Proceedings of the Machine Learning: ECML 2004, 2004

2002

Classification with Intersecting Rules.

Tony Lindgren, Henrik Boström

Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

2000

Anytime inductive logic programming.

Tony Lindgren

Proceedings of the ISCA 15th International Conference Computers and Their Applications, 2000