Publications

  • 2023

    A Workflow for Generating Patient Counterfactuals in Lung Transplant Recipients
    Rugolon, Franco, Bampa, Maria, and Papapetrou, Panagiotis
    In Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part II, 2023
    Surveillance of communicable diseases using social media: A systematic review
    Pilipiec, Patrick, Samsten, Isak, and Bota, András
    PLoS One, 2023
    Identification of essential genes associated with SARS-CoV-2 infection as potential drug target candidates with machine learning algorithms
    Taheri, Golnaz, and Habibi, Mahnaz
    Scientific Reports, 2023
    Improving and Analyzing Sketchy High-Fidelity Free-Eye Drawing
    Huang, Lida, Eladhari, Mirjam Palosaari, Magnússon, Sindri, Chen, Hao, and Guo, Ruijie
    In Proceedings of the 2023 ACM Designing Interactive Systems Conference, 2023
    A General Framework to Distribute Iterative Algorithms with Localized Information over Networks
    Timoudas, Thomas Ohlson, Zhang, Silun, Magnússon, Sindri, and Fischione, Carlo
    IEEE Transactions on Automatic Control, 2023
    Adaptive Hyperparameter Selection for Differentially Private Gradient Descent
    Fay, Dominik, Magnússon, Sindri, Sjölund, Jens, and Johansson, Mikael
    Transactions on Machine Learning Research, 2023
    Automotive fault nowcasting with machine learning and natural language processing
    Pavlopoulos, John, Romell, Alv, Curman, Jacob, Steinert, Olof, Lindgren, Tony, Borg, Markus, and Randl, Korbinian
    Machine Learning, 2023
    Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics
    Sun, Kaiji, Magnússon, Sindri, Steinert, Olof, and Lindgren, Tony
    In 2023 IEEE International Conference on Prognostics and Health Management (ICPHM), 2023
    Conditioned Fully Convolutional Denoising Autoencoder for Energy Disaggregation
    Garcı́a, Diego, Pérez, Daniel, Papapetrou, Panagiotis, Dı́az, Ignacio, Cuadrado, Abel A, Enguita, José Maria, González, Ana, and Domı́nguez, Manuel
    In IFIP International Conference on Artificial Intelligence Applications and Innovations, 2023
    Enterprise Modeling for Machine Learning: Case-Based Analysis and Initial Framework Proposal
    Bork, Dominik, Papapetrou, Panagiotis, and Zdravkovic, Jelena
    In International Conference on Research Challenges in Information Science, 2023
    Z-Time: efficient and effective interpretable multivariate time series classification
    Lee, Zed, Lindgren, Tony, and Papapetrou, Panagiotis
    Data mining and knowledge discovery, 2023
    Bridging the Gap: A Comparative Analysis of Regressive Remaining Useful Life Prediction and Survival Analysis Methods for Predictive Maintenance
    Rahat, Mahmoud, Kharazian, Zahra, Mashhadi, Peyman Sheikholharam, Rögnvaldsson, Thorsteinn, and Choudhury, Shamik
    In PHM Society Asia-Pacific Conference, 2023
    Intelligent Processing of Data Streams on the Edge Using Reinforcement Learning
    Vaishnav, Shubham, and Magnússon, Sindri
    In IEEE ICC 2023 Workshop on Scalable and Trustworthy AI for 6G Wireless Networks (6GSTRAIN), 2023
    Energy-Efficient and Adaptive Gradient Sparsification for Federated Learning
    Vaishnav, Shubham, Efthymiou, Maria, and Magnússon, Sindri
    In ICC 2023-IEEE International Conference on Communications, 2023
    Machine learning models for automated interpretation of 12-lead electrocardiographic signals: a narrative review of techniques, challenges, achievements and clinical relevance
    Pantelidis, Panteleimon, Bampa, Maria, Oikonomou, Evangelos, and Papapetrou, Panagiotis
    Journal of Medical Artificial Intelligence, 2023
    Early prediction of the risk of ICU mortality with Deep Federated Learning
    Randl, Korbinian, Armengol, Núria Lladós, Mondrejevski, Lena, and Miliou, Ioanna
    In 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), 2023
    Comparing NARS and Reinforcement Learning: An Analysis of ONA and Q-Learning Algorithms
    Beikmohammadi, Ali, and Magnússon, Sindri
    In International Conference on Artificial General Intelligence, 2023
    Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies
    Movin, Maria, Junior, Guilherme Dinis, Hollmén, Jaakko, and Papapetrou, Panagiotis
    In Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings, 2023
    Finding Local Groupings of Time Series
    Lee, Zed, Trincavelli, Marco, and Papapetrou, Panagiotis
    In Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part VI, 2023
    Distributed safe resource allocation using barrier functions
    Wu, Xuyang, Magnússon, Sindri, and Johansson, Mikael
    Automatica, 2023
    AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, a Framework Based on Active Learning and Transfer Learning
    Kharazian, Zahra, Rahat, Mahmoud, Gama, Fábio, Mashhadi, Peyman Sheikholharam, Nowaczyk, Sławomir, Lindgren, Tony, and Magnússon, Sindri
    In Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings, 2023
    Demonstrator on Counterfactual Explanations for Differentially Private Support Vector Machines
    Mochaourab, Rami, Sinha, Sugandh, Greenstein, Stanley, and Papapetrou, Panagiotis
    In Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part VI, 2023
    Personalized Feature Importance Ranking for Affect Recognition From Behavioral and Physiological Data
    Quintero, Luis, Fors, Uno, and Papapetrou, Panagiotis
    IEEE Transactions on Games, 2023
    Eyes can draw: A high-fidelity free-eye drawing method with unimodal gaze control
    Huang, Lida, Westin, Thomas, Eladhari, Mirjam Palosaari, Magnússon, Sindri, and Chen, Hao
    International Journal of Human-Computer Studies, 2023
    Style-transfer counterfactual explanations: An application to mortality prevention of ICU patients
    Wang, Zhendong, Samsten, Isak, Kougia, Vasiliki, and Papapetrou, Panagiotis
    Artificial Intelligence in Medicine, 2023
    Improved Step-Size Schedules for Proximal Noisy Gradient Methods
    Khirirat, Sarit, Wan, Xiaoyu, Magnússon, Sindri, and Johansson, Mikael
    IEEE Transactions on Signal Processing, 2023
    Measuring the Burden of (Un) fairness Using Counterfactuals
    Kuratomi, Alejandro, Pitoura, Evaggelia, Papapetrou, Panagiotis, Lindgren, Tony, and Tsaparas, Panayiotis
    In Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part I, 2023
    Predicting Drug Treatment for Hospitalized Patients with Heart Failure
    Zhou, Linyi, and Miliou, Ioanna
    In Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part II, 2023
    COVID-19 detection from thermal image and tabular medical data utilizing multi-modal machine learning
    Alam, Mahbub Ul, Hollmén, Jaakko, and Rahmani, Rahim
    In 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), 2023

    2022

    Understanding peace through the world news
    Voukelatou, Vasiliki, Miliou, Ioanna, Giannotti, Fosca, and Pappalardo, Luca
    EPJ Data Science, 2022
    Semi-parametric Approach to Random Forests for High-Dimensional Bayesian Optimisation
    Kuzmanovski, Vladimir, and Hollmén, Jaakko
    In Discovery Science: 25th International Conference, DS 2022, Montpellier, France, October 10–12, 2022, Proceedings, 2022
    Policy Evaluation with Delayed, Aggregated Anonymous Feedback
    Dinis Jr, Guilherme, Magnússon, Sindri, and Hollmén, Jaakko
    In International Conference on Discovery Science, 2022
    Inside the “brain” of an artificial neural network: an interpretable deep learning approach to paroxysmal atrial fibrillation diagnosis from electrocardiogram signals during sinus rhythm
    Pantelidis, P, Oikonomou, E, Lampsas, S, Souvaliotis, N, Spartalis, M, Vavuranakis, MA, Bampa, M, Papapetrou, P, Siasos, G, and Vavuranakis, M
    European Heart Journal, 2022
    Random subspace and random projection nearest neighbor ensembles for high dimensional data
    Deegalla, Sampath, Walgama, Keerthi, Papapetrou, Panagiotis, and Boström, Henrik
    Expert systems with applications, 2022
    Low dimensional synthetic data generation for improving data driven prognostic models
    Lindgren, Tony, and Steinert, Olof
    In 2022 IEEE International Conference on Prognostics and Health Management (ICPHM), 2022
    Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning
    Bull, L. A., Francesco, D. Di, Dhada, M., Steinert, O., Lindgren, Tony, Parlikad, A. K., Duncan, A. B., and Girolami, M.
    Computer-Aided Civil and Infrastructure Engineering, 2022
    SWP-LeafNET: A novel multistage approach for plant leaf identification based on deep CNN
    Beikmohammadi, Ali, Faez, Karim, and Motallebi, Ali
    Expert Systems with Applications, 2022
    Excite-O-Meter: an Open-Source Unity Plugin to Analyze Heart Activity and Movement Trajectories in Custom VR Environments
    Quintero, Luis, Papapetrou, Panagiotis, Muñoz, John E., Mooij, Jeroen, and Gaebler, Michael
    In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2022
    CS:NO – an Extended Reality Experience for Cyber Security Education
    Bernsland, Melina, Moshfegh, Arvin, Lindén, Kevin, Bajin, Stefan, Quintero, Luis, Solsona Belenguer, Jordi, and Rostami, Asreen
    In ACM International Conference on Interactive Media Experiences, 2022
    Prediction of environmental controversies and development of a corporate environmental performance rating methodology
    Svanberg, Jan, Ardeshiri, Tohid, Samsten, Isak, Öhman, Peter, Rana, Tarek, and Danielson, Mats
    Journal of Cleaner Production, 2022
    JUICE: JUstIfied Counterfactual Explanations
    Kuratomi, Alejandro, Miliou, Ioanna, Lee, Zed, Lindgren, Tony, and Papapetrou, Panagiotis
    In International Conference on Discovery Science, 2022
    Post-Hoc Explainability for Time Series Classification: Toward a signal processing perspective
    Mochaourab, Rami, Venkitaraman, Arun, Samsten, Isak, Papapetrou, Panagiotis, and Rojas, Cristian R.
    IEEE Signal Processing Magazine, 2022
    Corporate governance performance ratings with machine learning
    Svanberg, Jan, Ardeshiri, Tohid, Samsten, Isak, Öhman, Peter, Neidermeyer, Presha E., Rana, Tarek, Semenova, Natalia, and Danielson, Mats
    Intelligent Systems in Accounting, Finance and Management, 2022
    Interactive Painting Volumetric Cloud Scenes with Simple Sketches Based on Deep Learning
    Huang, Lida, Eladhari, Mirjam Palosaari, Magnússon, Sindri, Westin, Thomas, and Su, Nanxu
    In 2022 15th International Conference on Human System Interaction (HSI), 2022
    Leakage Localization in Water Distribution Networks: A Model-Based Approach
    Lindström, Ludvig, Gracy, Sebin, Magnússon, Sindri, and Sandberg, Henrik
    In 2022 European Control Conference (ECC), 2022
    Eco-Fedsplit: Federated Learning with Error-Compensated Compression
    Khirirat, Sarit, Magnússon, Sindri, and Johansson, Mikael
    In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022
    Weibull recurrent neural networks for failure prognosis using histogram data
    Dhada, Maharshi, Parlikad, Ajith Kumar, Steinert, Olof, and Lindgren, Tony
    Neural Computing and Applications, 2022
    Optimising and validating deep learning approaches for diagnosing atrial fibrillation from few-lead ambulatory electrocardiogram signals
    Pantelidis, P, Oikonomou, E, Souvaliotis, N, Spartalis, M, Bampa, Maria, Papapetrou, Panagiotis, Siasos, G, and Vavuranakis, M
    Europace, 2022
    EpidRLearn: Learning Intervention Strategies for Epidemics with Reinforcement Learning
    Bampa, Maria, Fasth, Tobias, Magnússon, Sindri, and Papapetrou, Panagiotis
    In Artificial Intelligence in Medicine, 2022
    FLICU: A Federated Learning Workflow for Intensive Care Unit Mortality Prediction
    Mondrejevski, Lena, Miliou, Ioanna, Montanino, Annaclaudia, Pitts, David, Hollmén, Jaakko, and Papapetrou, Panagiotis
    In 2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS), 2022
    Impact of Dimensionality on Nowcasting Seasonal Influenza with Environmental Factors
    Guarnizo, Stefany, Miliou, Ioanna, and Papapetrou, Panagiotis
    In International Symposium on Intelligent Data Analysis, 2022
    Principal Component Analysis Visualizations in State Discovery by Animating Exploration Results
    Sirola, Miki, Rinta-Koski, Olli-Pekka, Nguyen, Le Ngu, and Hollmén, Jaakko
    In 2022 IEEE International Conference on Smart Computing (SMARTCOMP), 2022

    2021

    A Flexible Framework for Communication-Efficient Machine Learning
    Khirirat, Sarit, Magnússon, Sindri, Aytekin, Arda, and Johansson, Mikael
    Proceedings of the AAAI Conference on Artificial Intelligence, 2021
    RTEX: A novel framework for ranking, tagging, and explanatory diagnostic captioning of radiography exams
    Kougia, Vasiliki, Pavlopoulos, John, Papapetrou, Panagiotis, and Gordon, Max
    Journal of the American Medical Informatics Association, 2021
    Automatic and Intelligent Recommendations to Support Students’ Self-Regulation
    Afzaal, Muhammad, Nouri, Jalal, Zia, Aayesha, Papapetrou, Panagiotis, Fors, Uno, Wu, Yongchao, Li, Xiu, and Weegar, Rebecka
    In 2021 International Conference on Advanced Learning Technologies (ICALT), 2021
    Automated Grading of Exam Responses: An Extensive Classification Benchmark
    Ljungman, Jimmy, Lislevand, Vanessa, Pavlopoulos, John, Farazouli, Alexandra, Lee, Zed, Papapetrou, Panagiotis, and Fors, Uno
    In International Conference on Discovery Science, 2021
    Energy and Resource Efficiency by User Traffic Prediction and Classification in Cellular Networks
    Azari, Amin, Salehi, Fateme, Papapetrou, Panagiotis, and Cavdar, Cicek
    IEEE Transactions on Green Communications and Networking, 2021
    State Discovery and Prediction from Multivariate Sensor Data
    Rinta-Koski, Olli-Pekka, Sirola, Miki, Nguyen, Le Ngu, and Hollmén, Jaakko
    In Advanced Analytics and Learning on Temporal Data, 2021
    Early oxygen levels contribute to brain injury in extremely preterm infants
    Rantakari, Krista, Rinta-Koski, Olli-Pekka, Metsäranta, Marjo, Hollmén, Jaakko, Särkkä, Simo, Rahkonen, Petri, Lano, Aulikki, Lauronen, Leena, Nevalainen, Päivi, Leskinen, Markus J, and others,
    Pediatric Research, 2021
    Composite Surrogate for Likelihood-Free Bayesian Optimisation in High-Dimensional Settings of Activity-Based Transportation Models
    Kuzmanovski, Vladimir, and Hollmén, Jaakko
    In International Symposium on Intelligent Data Analysis, 2021
    Hybrid Feature Tweaking: Combining Random Forest Similarity Tweaking with CLPFD
    Lindgren, Tony
    In 2021 7th International Conference on Computing and Data Engineering, 2021
    Learning Time Series Counterfactuals via Latent Space Representations
    Wang, Zhendong, Samsten, Isak, Mochaourab, Rami, and Papapetrou, Panagiotis
    In International Conference on Discovery Science, 2021
    Assessing the Clinical Validity of Attention-based and SHAP Temporal Explanations for Adverse Drug Event Predictions
    Rebane, Jonathan, Samsten, Isak, Pantelidis, Panteleimon, and Papapetrou, Panagiotis
    In 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), 2021
    Sentiment Nowcasting During the COVID-19 Pandemic
    Miliou, Ioanna, Pavlopoulos, John, and Papapetrou, Panagiotis
    In International Conference on Discovery Science, 2021
    Predicting seasonal influenza using supermarket retail records
    Miliou, Ioanna, Xiong, Xinyue, Rinzivillo, Salvatore, Zhang, Qian, Rossetti, Giulio, Giannotti, Fosca, Pedreschi, Dino, and Vespignani, Alessandro
    PLOS Computational Biology, 2021
    Effective Classification of Head Motion Trajectories in Virtual Reality using Time-Series Methods
    Quintero, Luis, Papapetrou, Panagiotis, Hollmén, Jaakko, and Fors, Uno
    In IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), 2021
    Excite-O-Meter: Software Framework to Integrate Heart Activity in Virtual Reality
    Quintero, Luis, Muñoz, John E, Mooji, Jeroen, and Gaebler, Michael
    In IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2021
    Measuring objective and subjective well-being: dimensions and data sources
    Voukelatou, Vasiliki, Gabrielli, Lorenzo, Miliou, Ioanna, Cresci, Stefano, Sharma, Rajesh, Tesconi, Maurizio, and Pappalardo, Luca
    International Journal of Data Science and Analytics, 2021
    A New Family of Feasible Methods for Distributed Resource Allocation
    Wu, Xuyang, Magnússon, Sindri, and Johansson, Mikael
    In 2021 60th IEEE Conference on Decision and Control (CDC), 2021
    On the Convergence of Step Decay Step-Size for Stochastic Optimization
    Wang, Xiaoyu, Magnússon, Sindri, and Johansson, Mikael
    In Advances in Neural Information Processing Systems, 2021
    Improved Step-Size Schedules for Noisy Gradient Methods
    Khirirat, Sarit, Wang, Xiaoyu, Magnússon, Sindri, and Johansson, Mikael
    In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
    Distributed Newton Method Over Graphs: Can Sharing of Second-Order Information Eliminate the Condition Number Dependence?
    Berglund, Erik, Magnússon, Sindri, and Johansson, Mikael
    IEEE Signal Processing Letters, 2021
    Compressed Gradient Methods with Hessian-Aided Error Compensation
    Khirirat, S., Magnússon, S., and Johansson, M.
    IEEE Transactions on Signal Processing, 2021
    Guest editorial: Special issue on mining for health
    Spiliopoulou, Myra, and Papapetrou, Panagiotis
    Data Min. Knowl. Discov., 2021
    Counterfactual Explanations for Survival Prediction of Cardiovascular ICU Patients
    Wang, Zhendong, Samsten, Isak, and Papapetrou, Panagiotis
    In Artificial Intelligence in Medicine (AIME), 2021
    Customized Neural Predictive Medical Text: A Use-Case on Caregivers
    Pavlopoulos, John, and Papapetrou, Panagiotis
    In Artificial Intelligence in Medicine (AIME), 2021
    Z-Hist: A Temporal Abstraction of Multivariate Histogram Snapshots
    Lee, Zed, Anton, Nicholas, Papapetrou, Panagiotis, and Lindgren, Tony
    In International Symposium on Intelligent Data Analysis (IDA), 2021
    A flexible framework for communication-efficient machine learning
    Khirirat, S., Magnússon, S., Aytekin, A., and Johansson, M.
    In Proceedings of The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021
    Explainable AI for data-driven feedback and intelligent action recommendations to support students self-regulation
    Afzaal, Muhammad, Nouri, Jalal, Zia, Aayesha, Papapetrou, Panagiotis, Fors, Uno, Wu, Yongchao, Li, Xiu, and Weegar, Rebecka
    Frontiers in Artificial Intelligence, 2021
    SMILE: a feature-based temporal abstraction framework for event-interval sequence classification
    Rebane, Jonathan, Karlsson, Isak, Bornemann, Leon, and Papapetrou, Panagiotis
    Data Mining and Knowledge Discovery, 2021
    Generation of automatic data-driven feedback to students using Explainable Machine Learning
    Afzaal, Muhammad, Nouri, Jalal, Zia, Aayesha, Papapetrou, Panagiotis, Fors, Uno, Wu, Yongchao, Li, Xiu, and Weegar, Rebecka
    In International Conference on Artificial Intelligence in Education, 2021

    2020

    ERRANT: Assessing and Improving Grammatical Error Type Classification
    Korre, Katerina, and Pavlopoulos, John
    In In the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, 2020
    Mitigating discrimination in clinical machine learning decision support using algorithmic processing techniques
    Briggs, Emma, and Hollmén, Jaakko
    In International Conference on Discovery Science, 2020
    Machine learning methods for neonatal mortality and morbidity classification
    Jaskari, Joel, Myllärinen, Janne, Leskinen, Markus, Rad, Ali Bahrami, Hollmén, Jaakko, Andersson, Sture, and Särkkä, Simo
    IEEE Access, 2020
    Evaluation of Dimensionality Reduction Techniques-Principal Feature Analysis in Case of Text Classification Problems
    Mammo, Michael, and Lindgren, Tony
    In , 2020
    Z-Embedding: A Spectral Representation of Event Intervals for Efficient Clustering and Classification
    Lee, Zed, Girdzijauskas, Šarūnas, and Papapetrou, Panagiotis
    In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2020
    Prediction of Global Navigation Satellite System Positioning Errors with Guarantees
    Kuratomi, Alejandro, Lindgren, Tony, and Papapetrou, Panagiotis
    In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2020
    Detecting Adverse Drug Events from Swedish Electronic Health Records using Text Mining
    Bampa, Maria, and Dalianis, Hercules
    In Proceedings of the LREC 2020 Workshop on Multilingual Biomedical Text Processing (MultilingualBIO 2020), 2020
    Estimating countries’ peace index through the lens of the world news as monitored by GDELT
    Voukelatou, Vasiliki, Pappalardo, Luca, Miliou, Ioanna, Gabrielli, Lorenzo, and Giannotti, Fosca
    In 2020 IEEE 7th international conference on data science and advanced analytics (DSAA), 2020
    On Maintaining Linear Convergence of Distributed Learning and Optimization under Limited Communication
    Magnússon, Sindri, Shokri-Ghadikolaei, Hossein, and Li, Na
    IEEE Transactions on Signal Processing, 2020
    The Internet of Things as a Deep Neural Network
    Du, R., Magnússon, S., and Fischione, C.
    IEEE Communications Magazine, Internet of Things and Sensor Networks Series, 2020
    Distributed Optimal Voltage Control with Asynchronous and Delayed Communication
    Magnússon, Sindri, Qu, G., and Li, N.
    IEEE Transactions on Smart Grid, 2020
    Communication-Efficient Variance-Reduced Stochastic Gradient Descent
    Shokri-Ghadikolaei, H., and Magnússon, S.
    In Proceedings of the IFAC World Congress, 2020
    Locally and globally explainable time series tweaking
    Karlsson, Isak, Rebane, Jonathan, Papapetrou, Panagiotis, and Gionis, Aristides
    Knowledge and Information Systems, 2020
    Corrigendum to ’Learning from heterogeneous temporal data in electronic health records’. [J. Biomed. Inform. 65 (2017) 105-119]
    Zhao, Jing, Papapetrou, Panagiotis, Asker, Lars, and Bostrom, Henrik
    J. Biomed. Informatics, 2020
    Exploiting complex medical data with interpretable deep learning for adverse drug event prediction
    Rebane, Jonathan, Samsten, Isak, and Papapetrou, Panagiotis
    Artificial Intelligence in Medicine, 2020
    Evaluating Local Interpretable Model-Agnostic Explanations on Clinical Machine Learning Classification Models
    Barr Kumarakulasinghe, Nesaretnam, Blomberg, Tobias, Liu, Jintai, Saraiva Leao, Alexandra, and Papapetrou, Panagiotis
    In International Symposium on Computer-Based Medical Systems (CBMS), 2020
    A Clustering Framework for Patient Phenotyping with Application to Adverse Drug Events
    Bampa, Maria, Papapetrou, Panagiotis, and Hollmén, Jaakko
    In International Symposium on Computer-Based Medical Systems (CBMS), 2020
    Mining Disproportional Frequent Arrangements of Event Intervals for Investigating Adverse Drug Events
    Lee, Zed, Rebane, Jonathan, and Papapetrou, Panagiotis
    In International Symposium on Computer-Based Medical Systems (CBMS), 2020
    Z-Miner: An Efficient Method for Mining Frequent Arrangements of Event Intervals
    Lee, Zed, Lindgren, Tony, and Papapetrou, Panagiotis
    In International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020
    Clinical Predictive Keyboard using Statistical and Neural Language Modeling
    Pavlopoulos, John, and Papapetrou, Panagiotis
    In International Symposium on Computer-Based Medical Systems (CBMS), 2020
    A Psychophysiological Model of Firearms Training in Police Officers : A Virtual Reality Experiment for Biocybernetic Adaptation
    Muñoz, John E, Quintero, Luis, Stephens, Chad L, and Pope, Alan T
    Frontiers in Psychology, 2020
    Understanding Research Methodologies when Combining Virtual Reality Technology with Machine Learning Techniques
    Quintero, Luis
    In International Conference on PErvasive Technologies Related to Assistive Environments (PETRA), 2020
    Medical Image Tagging by Deep Learning and Retrieval
    Kougia, Vasiliki, Pavlopoulos, John, and Androutsopoulos, Ion
    In International Conference of the Cross-Language Evaluation Forum for European Languages, 2020
    An Interactive Visual Tool to Enhance Understanding of Random Forest Predictions
    Gurung, Ram B., Lindgren, Tony, and Boström, Henrik
    Archives of Data Science, Series A (Online First), 2020

    2019

    Cellular Traffic Prediction and Classification: A Comparative Evaluation of LSTM and ARIMA
    Azari, Amin, Papapetrou, Panagiotis, Denic, Stojan Z., and Peters, Gunnar
    In In International Conference on Discovery Science (DS), 2019
    Voltage Control Using Limited Communication
    Magnússon, S., Qu, G., Fischione, C., and Li, N.
    IEEE Transactions on Control of Network Systems, 2019
    On Maintaining Linear Convergence of Distributed Learning and Optimization under Limited Communication
    Magnússon, S., Shokri-Ghadikolaei, H., and N. Li,
    In Proceedings of the 53rd IEEE Asilomar Conference on Signals, Systems, and Computers, 2019
    Distributed Optimal Voltage Control with Delayed Communication
    Magnússon, S., Qu, G., and Li, N.
    In Proceedings of the IEEE American Control Conference (ACC), 2019
    Optimal voltage control using event triggered communication
    Magnússon, Sindri, Fischione, Carlo, and Li, Na
    In Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019
    Convergence Bounds For Compressed Gradient Methods With Memory Based Error Compensation
    Khirirat, S., Magnússon, S., and Johansson, M.
    In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
    An Investigation of Interpretable Deep Learning for Adverse Drug Event Prediction
    Rebane, Jonathan, Karlsson, Isak, and Papapetrou, Panagiotis
    In International Symposium on Computer-Based Medical Systems (CBMS), 2019
    A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records
    Bagattini, Francesco, Karlsson, Isak, Rebane, Jonathan, and Papapetrou, Panagiotis
    BMC Medical Informatics Decis. Mak., 2019
    Mining and Model Understanding on Medical Data
    Spiliopoulou, Myra, and Papapetrou, Panagiotis
    In International Conference on Knowledge Discovery & Data Mining (KDD), 2019
    Example-Based Feature Tweaking Using Random Forests
    Lindgren, Tony, Papapetrou, Panagiotis, Samsten, Isak, and Asker, Lars
    In International Conference on Information Reuse and Integration for Data Science (IRI), 2019
    FISUL: A Framework for Detecting Adverse Drug Events from Heterogeneous Medical Sources Using Feature Importance
    Allaart, Corinne G., Mondrejevski, Lena, and Papapetrou, Panagiotis
    In International Conference on Artificial Intelligence Applications and Innovations (AIAI), 2019
    Clustering Diagnostic Profiles of Patients
    Hollmén, Jaakko, and Papapetrou, Panagiotis
    In International Conference on Artificial Intelligence Applications and Innovations (AIAI), 2019
    Mining Adverse Drug Events Using Multiple Feature Hierarchies and Patient History Windows
    Bampa, Maria, and Papapetrou, Panagiotis
    In International Conference on Data Mining Workshops (ICDMW), 2019
    User Traffic Prediction for Proactive Resource Management: Learning-Powered Approaches
    Azari, Amin, Papapetrou, Panagiotis, Denic, Stojan Z., and Peters, Gunnar
    In Global Communications Conference (GLOBECOM), 2019
    Cellular Traffic Prediction and Classification: A Comparative Evaluation of LSTM and ARIMA
    Azari, Amin, Papapetrou, Panagiotis, Denic, Stojan Z., and Peters, Gunnar
    In International Conference on Discovery Science (DS), 2019
    Implementation of Mobile-Based Real-Time Heart Rate Variability Detection for Personalized Healthcare
    Quintero, Luis, Papapetrou, Panagiotis, Muñoz, John E., and Fors, Uno
    In International Conference on Data Mining Workshops (ICDMW), 2019
    Integrating Biocybernetic Adaptation in Virtual Reality Training Concentration and Calmness in Target Shooting
    Muñoz, John E, Pope, Alan T, and Quintero, Luis
    Physiological Computing Systems, 2019
    Open-Source Physiological Computing Framework using Heart Rate Variability in Mobile Virtual Reality Applications
    Quintero, Luis, Papapetrou, Panagiotis, and Muñoz, John E
    In International Conference on Artificial Intelligence and Virtual Reality (AIVR), 2019
    A Survey on Biomedical Image Captioning
    Kougia, Vasiliki, Pavlopoulos, John, and Androutsopoulos, Ion
    arXiv preprint arXiv:1905.13302, 2019
    Convai at semeval-2019 task 6: Offensive language identification and categorization with perspective and bert
    Pavlopoulos, John, Thain, Nithum, Dixon, Lucas, and Androutsopoulos, Ion
    In Proceedings of the 13th International Workshop on Semantic Evaluation, 2019
    A Survey on Biomedical Image Captioning
    Pavlopoulos, John, Kougia, Vasiliki, and Androutsopoulos, Ion
    In Proceedings of the Second Workshop on Shortcomings in Vision and Language, 2019
    User Traffic Prediction for Proactive Resource Management: Learning-Powered Approaches
    Azari, Amin, Papapetrou, Panagiotis, Denic, Stojan Z., and Peters, Gunnar
    In In Global Communications Conference (GLOBECOM), 2019
    Temporal Analysis of Adverse Weather Conditions Affecting Wheat Production in Finland
    Kuzmanovski, Vladimir, Sulkava, Mika, Palosuo, Taru, and Hollmén, Jaakko
    In International Conference on Discovery Science, 2019

    2018

    Communication Complexity of Dual Decomposition Methods for Distributed Resource Allocation Optimization
    Magnússon, S., Enyioha, C., Li, N., Fischione, C., and Tarokh, V.
    IEEE Journal of Selected Topics in Signal Processing, 2018
    Convergence of Limited Communications Gradient Methods
    Magnússon, S., Enyioha, C., Li, N., Fischione, C., and Tarokh, V.
    IEEE Transactions on Automatic Control, 2018
    On Variability of Renewable Energy and Online Power Allocation
    Enyioha, C., Magnússon, S., Li, N., Fischione, C., and Tarokh, V.
    IEEE Transactions on Power Systems, 2018
    Information-Entropy-Based DNS Tunnel Prediction
    Homem, Irvin, Papapetrou, Panagiotis, and Dosis, Spyridon
    In Advances in Digital Forensics XIV, 2018
    Discovering, selecting and exploiting feature sequence records of study participants for the classification of epidemiological data on hepatic steatosis
    Hielscher, Tommy, Volzke, Henry, Papapetrou, Panagiotis, and Spiliopoulou, Myra
    In Symposium on Applied Computing (SAC), 2018
    Explainable Predictions of Adverse Drug Events from Electronic Health Records Via Oracle Coaching
    Crielaard, Loes, and Papapetrou, Panagiotis
    In International Conference on Data Mining Workshops (ICDMW), 2018
    Explainable time series tweaking via irreversible and reversible temporal transformations
    Karlsson, Isak, Rebane, Jonathan, Papapetrou, Panagiotis, and Gionis, Aristides
    In International Conference on Data Mining (ICDM), 2018

    2017

    Voltage Control Using Limited Communication
    Magnússon, S., Fischione, C., and Li, N.
    In Proceedings of the IFAC 2017 World Congress, 2017
    Kapminer: Mining ordered association rules with constraints
    Karlsson, Isak, Papapetrou, Panagiotis, and Asker, Lars
    In International Symposium on Intelligent Data Analysis, 2017
    On searching and indexing sequences of temporal intervals
    Kostakis, Orestis, and Papapetrou, Panagiotis
    Data Min. Knowl. Discov., 2017
    Learning from heterogeneous temporal data in electronic health records
    Zhao, Jing, Papapetrou, Panagiotis, Asker, Lars, and Boström, Henrik
    J. Biomed. Informatics, 2017
    ABIDE: Querying Time-Evolving Sequences of Temporal Intervals
    Kostakis, Orestis, and Papapetrou, Panagiotis
    In International Symposium on Intelligent Data Analysis (IDA), 2017
    Conformal Prediction Using Random Survival Forests
    Boström, Henrik, Asker, Lars, Gurung, Ram B., Karlsson, Isak, Lindgren, Tony, and Papapetrou, Panagiotis
    In EEE International Conference on Machine Learning and Applications, ICMLA 2017, Cancun, Mexico, December 18-21, 2017, 2017

    2016

    Generalized random shapelet forests
    Karlsson, Isak, Papapetrou, Panagiotis, and Boström, Henrik
    Data Min. Knowl. Discov., 2016
    On the Convergence of Alternating Direction Lagrangian Methods for Nonconvex Structured Optimization Problems
    Magnússon, S., Weeraddana, P. C., Rabbat, M. G., and Fischione, C.
    IEEE Transactions on Control of Network Systems, 2016
    A Distributed Approach for the Optimal Power Flow Problem Based on ADMM and Sequential Convex Approximations
    Magnússon, S., Weeraddana, P. C., and Fischione, C.
    IEEE Transactions on Control of Network Systems, 2016
    Practical Coding Schemes For Bandwidth Limited One-Way Communication Resource Allocation
    Magnússon, S., Enyioha, C., Fischione, C., and Li, N.
    In Proceedings of the 56th IEEE Conference on Decision and Control (CDC), 2016
    Convergence of Limited Communications Gradient Method
    Magnússon, S., Enyioha, C., Li, N., Fischione, C., and Tarokh, V.
    In Proceedings of the IEEE American Control Conference (ACC), 2016
    On Some Extensions of Fast-Lipschitz Optimization
    S. Magnússon, C. Fischione, and Weeraddana, P. C.
    In Proceedings of the IEEE European Control Conference (ECC), 2016
    A Distributed Approach for the Optimal Power Flow Problem
    Magnússon, S., Fischione, C., and Weeraddana, P. C.
    In Proceedings of the IEEE European Control Conference (ECC), 2016
    Distributed Resource Allocation Using One-Way Communication with Applications to Power Networks
    Magnússon, S., Enyioha, C., Heal, K., Li, N., Fischione, C., and Tarokh, V.
    In Proceedings of the IEEE 50th Annual Conference on Information Sciences and Systems (CISS), 2016
    Analysis for an Online Decentralized Descent Power allocation algorithm
    Enyioha, C., Magnússon, S., Heal, K., Li, N., Fischione, C., and Tarokh, V.
    In Proceedings of the IEEE Information Theory and Applications Workshop (ITA), 2016
    Generalized random shapelet forests
    Karlsson, Isak, Papapetrou, Panagiotis, and Boström, Henrik
    Data mining and knowledge discovery, 2016
    Early random shapelet forest
    Karlsson, Isak, Papapetrou, Panagiotis, and Boström, Henrik
    In International Conference on Discovery Science (DS), 2016
    Identifying Factors for the Effectiveness of Treatment of Heart Failure: A Registry Study
    Asker, Lars, Boström, Henrik, Papapetrou, Panagiotis, and Persson, Hans E.
    In nternational Symposium on Computer-Based Medical Systems (CBMS), 2016
    STIFE: A Framework for Feature-Based Classification of Sequences of Temporal Intervals
    Bornemann, Leon, Lecerf, Jason, and Papapetrou, Panagiotis
    In Discovery Science - 19th International Conference, DS 2016, Bari, Italy, October 19-21, 2016, Proceedings, 2016
    Semigeometric Tiling of Event Sequences
    Henelius, Andreas, Karlsson, Isak, Papapetrou, Panagiotis, Ukkonen, Antti, and Puolamäki, Kai
    In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I, 2016
    Significance testing of word frequencies in corpora
    Lijffijt, Jefrey, Nevalainen, Terttu, Säily, Tanja, Papapetrou, Panagiotis, Puolamäki, Kai, and Mannila, Heikki
    Digit. Scholarsh. Humanit., 2016
    Semigeometric Tiling of Event Sequences
    Henelius, Andreas, Karlsson, Isak, Papapetrou, Panagiotis, Ukkonen, Antti, and Puolamäki, Kai
    In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I, 2016
    A Multi-Granularity Pattern-Based Sequence Classification Framework for Educational Data
    Jaber, Mohammad, Wood, Peter T., Papapetrou, Panagiotis, and González-Marcos, Ana
    In IEEE International Conference on Data Science and Advanced Analytics, DSAA 2016, Montreal, QC, Canada, October 17-19, 2016, 2016
    Query-sensitive distance measure selection for time series nearest neighbor classification
    Kotsifakos, Alexios, Athitsos, Vassilis, and Papapetrou, Panagiotis
    Intell. Data Anal., 2016
    Extensions of Fast-Lipschitz Optimization
    Jakobsson, M., Magnússon, S., Fischione, C., and Weeraddana, P. C.
    IEEE Transactions on Automatic Control, 2016

    2015

    Forests of Randomized Shapelet Trees
    Karlsson, Isak, Papapetrou, Panagiotis, and Boström, Henrik
    In Statistical Learning and Data Sciences - Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings, 2015
    Finding the longest common sub-pattern in sequences of temporal intervals
    Kostakis, Orestis, and Papapetrou, Panagiotis
    Data Min. Knowl. Discov., 2015
    DRESS: dimensionality reduction for efficient sequence search
    Kotsifakos, Alexios, Stefan, Alexandra, Athitsos, Vassilis, Das, Gautam, and Papapetrou, Panagiotis
    Data Min. Knowl. Discov., 2015
    Size matters: choosing the most informative set of window lengths for mining patterns in event sequences
    Lijffijt, Jefrey, Papapetrou, Panagiotis, and Puolamäki, Kai
    Data Min. Knowl. Discov., 2015
    Embedding-based subsequence matching with gaps-range-tolerances: a Query-By-Humming application
    Kotsifakos, Alexios, Karlsson, Isak, Papapetrou, Panagiotis, Athitsos, Vassilis, and Gunopulos, Dimitrios
    VLDB Journal, 2015
    Analysing Online Education-based Asynchronous Communication Tools to Detect Students’ Roles
    Jaber, Mohammad, Papapetrou, Panagiotis, González-Marcos, Ana, and Wood, Peter T.
    In International Conference on Computer Supported Education (CSEDU), 2015
    Optimizing Hashing Functions for Similarity Indexing in Arbitrary Metric and Nonmetric Spaces
    Jangyodsuk, Pat, Papapetrou, Panagiotis, and Athitsos, Vassilis
    In Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30 - May 2, 2015, 2015
    GoldenEye++: A Closer Look into the Black Box
    Henelius, Andreas, Puolamäki, Kai, Karlsson, Isak, Zhao, Jing, Asker, Lars, Boström, Henrik, and Papapetrou, Panagiotis
    In Statistical Learning and Data Sciences - Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings, 2015
    On the Convergence of an Alternating Direction Penalty Method for Nonconvex Problems
    Magnússon, S., Weeraddana, P. C., Rabbat, M. G., and Fischione, C.
    In Proceedings of the IEEE 48th Asilomar Conference on Signals, Systems and Computers , 2015