Data Science Research Group: Publications

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

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