Tony Lindgren

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 28

Top Topics

Multivariate Time Series

Machine Learning

Hierarchical Bayesian

Dimensionality Reduction

Top Venues

Publications

John Pavlopoulos, Alv Romell, Jacob Curman, Olof Steinert, Tony Lindgren, Markus Borg, Korbinian Randl
Automotive fault nowcasting with machine learning and natural language processing. Mach. Learn. 113 (2) (2024)
Korbinian Randl, John Pavlopoulos, Aron Henriksson, Tony Lindgren
CICLe: Conformal In-Context Learning for Largescale Multi-Class Food Risk Classification. ACL (Findings) (2024)
Ali Beikmohammadi, Mohammad Hosein Hamian, Neda Khoeyniha, Tony Lindgren, Olof Steinert, Sindri Magnússon
A Cost-Sensitive Transformer Model for Prognostics Under Highly Imbalanced Industrial Data. CoRR (2024)
Zed Lee, Tony Lindgren, Panagiotis Papapetrou
Z-Time: efficient and effective interpretable multivariate time series classification. Data Min. Knowl. Discov. 38 (1) (2024)
Alejandro Kuratomi, Ioanna Miliou, Zed Lee, Tony Lindgren, Panagiotis Papapetrou
Ijuice: integer JUstIfied counterfactual explanations. Mach. Learn. 113 (8) (2024)
Korbinian Randl, John Pavlopoulos, Aron Henriksson, Tony Lindgren
Evaluating the Reliability of Self-Explanations in Large Language Models. CoRR (2024)
Zahra Kharazian, Tony Lindgren, Sindri Magnússon, Olof Steinert, Oskar Andersson Reyna
SCANIA Component X Dataset: A Real-World Multivariate Time Series Dataset for Predictive Maintenance. CoRR (2024)
Korbinian Randl, John Pavlopoulos, Aron Henriksson, Tony Lindgren
CICLe: Conformal In-Context Learning for Largescale Multi-Class Food Risk Classification. CoRR (2024)
Maharshi Harshadbhai Dhada, Ajith Kumar Parlikad, Olof Steinert, Tony Lindgren
Weibull recurrent neural networks for failure prognosis using histogram data. Neural Comput. Appl. 35 (4) (2023)
Lawrence A. Bull, Domenic Di Francesco, Maharshi Harshadbhai Dhada, Olof Steinert, Tony Lindgren, Ajith Kumar Parlikad, Andrew B. Duncan, Mark Girolami
Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning. Comput. Aided Civ. Infrastructure Eng. 38 (7) (2023)
Zahra Kharazian, Mahmoud Rahat, Fábio F. Gama, Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk, Tony Lindgren, Sindri Magnússon
AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, a Framework Based on Active Learning and Transfer Learning. IDA (2023)
Kaiji Sun, Sindri Magnússon, Olof Steinert, Tony Lindgren
Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics. ICPHM (2023)
Alejandro Kuratomi, Zed Lee, Ioanna Miliou, Tony Lindgren, Panagiotis Papapetrou
ORANGE: Opposite-label soRting for tANGent Explanations in heterogeneous spaces. DSAA (2023)
Tony Lindgren, Olof Steinert
Low dimensional synthetic data generation for improving data driven prognostic models. ICPHM (2022)
L. A. Bull, Maharshi Harshadbhai Dhada, Olof Steinert, Tony Lindgren, Ajith Kumar Parlikad, Andrew B. Duncan, Mark Girolami
Knowledge Transfer in Engineering Fleets: Hierarchical Bayesian Modelling for Multi-Task Learning. CoRR (2022)
John Pavlopoulos, Alv Romell, Jacob Curman, Olof Steinert, Tony Lindgren, Markus Borg
Automotive Multilingual Fault Diagnosis. CoRR (2022)
Alejandro Kuratomi, Ioanna Miliou, Zed Lee, Tony Lindgren, Panagiotis Papapetrou
JUICE: JUstIfied Counterfactual Explanations. DS (2022)
Alejandro Kuratomi, Evaggelia Pitoura, Panagiotis Papapetrou, Tony Lindgren, Panayiotis Tsaparas
Measuring the Burden of (Un)fairness Using Counterfactuals. PKDD/ECML Workshops (1) (2022)
Zed Lee, Nicholas Anton, Panagiotis Papapetrou, Tony Lindgren
Z-Hist: A Temporal Abstraction of Multivariate Histogram Snapshots. IDA (2021)
Zed Lee, Tony Lindgren, Panagiotis Papapetrou
Z-Miner: An Efficient Method for Mining Frequent Arrangements of Event Intervals. KDD (2020)
Alejandro Kuratomi, Tony Lindgren, Panagiotis Papapetrou
Prediction of Global Navigation Satellite System Positioning Errors with Guarantees. ECML/PKDD (4) (2020)
Michael Mammo, Tony Lindgren
Evaluation of Dimensionality Reduction Techniques-Principal Feature Analysis in case of Text Classification Problems. ICCDE (2020)
Gishan Don Ranasinghe, Tony Lindgren, Mark Girolami, Ajith Kumar Parlikad
A Methodology for Prognostics Under the Conditions of Limited Failure Data Availability. IEEE Access 7 (2019)
Tony Lindgren, Panagiotis Papapetrou, Isak Samsten, Lars Asker
Example-Based Feature Tweaking Using Random Forests. IRI (2019)
Tony Lindgren
On Data Driven Organizations and the Necessity of Interpretable Models. SGIoT (2018)
Tony Lindgren
Randomized Separate and Conquer Rule induction. ICCDA (2017)
Henrik Boström, Lars Asker, Ram B. Gurung, Isak Karlsson, Tony Lindgren, Panagiotis Papapetrou
Conformal Prediction Using Random Survival Forests. ICMLA (2017)
Ram B. Gurung, Tony Lindgren, Henrik Boström
Learning Decision Trees from Histogram Data Using Multiple Subsets of Bins. FLAIRS Conference (2016)
Tony Lindgren
Troubleshooting ECU Programmed by Bodybuilders. ICCVE (2012)
Tony Lindgren
On handling conflicts between rules with numerical features. SAC (2006)
Tony Lindgren
Methods for Rule Conflict Resolution. ECML (2004)
Tony Lindgren, Henrik Boström
Resolving rule conflicts with double induction. Intell. Data Anal. 8 (5) (2004)
Tony Lindgren, Henrik Boström
Resolving Rule Conflicts with Double Induction. IDA (2003)
Tony Lindgren, Henrik Boström
Classification with Intersecting Rules. ALT (2002)
Tony Lindgren
Anytime inductive logic programming. CATA (2000)