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Slawomir Nowaczyk
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2020 – today
- 2024
- [j30]Mohamed Abuella, M. Amine Atoui, Slawomir Nowaczyk, Simon Johansson, Ethan Faghani:
Spatial Clustering Approach for Vessel Path Identification. IEEE Access 12: 66248-66258 (2024) - [j29]Haroldas Razvadauskas, Evaldas Vaiciukynas, Kazimieras Buskus, Lukas Arlauskas, Slawomir Nowaczyk, Saulius Sadauskas, Albinas Naudziunas:
Exploring classical machine learning for identification of pathological lung auscultations. Comput. Biol. Medicine 168: 107784 (2024) - [j28]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi, Julia Handl:
Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks. Inf. Sci. 667: 120500 (2024) - [c54]Guojun Liang, Prayag Tiwari, Slawomir Nowaczyk, Stefan Byttner:
Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation. CIKM 2024: 1356-1366 - [c53]Slawomir Nowaczyk, Kurt Tutschku:
Message from Kurt Tutschku and Slawomir Nowaczyk, FMEC Chairs. FMEC 2024: 1 - [c52]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi, Julia Handl:
A Review of Randomness Techniques in Deep Neural Networks. GECCO Companion 2024: 23-24 - [c51]Mohammed Ghaith Altarabichi, Abdallah Alabdallah, Sepideh Pashami, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Mattias Ohlsson:
Improving Concordance Index in Regression-based Survival Analysis: Evolutionary Discovery of Loss Function for Neural Networks. GECCO Companion 2024: 1863-1869 - [c50]Yuantao Fan, Mohammed Ghaith Altarabichi, Sepideh Pashami, Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk:
Invariant Feature Selection for Battery State of Health Estimation in Heterogeneous Hybrid Electric Bus Fleets. HAII5.0@ECAI 2024 - [c49]Yuantao Fan, Zhenkan Wang, Sepideh Pashami, Slawomir Nowaczyk:
Evaluating Multi-task Curriculum Learning for Forecasting Energy Consumption in Electric Heavy-duty Vehicles. HAII5.0@ECAI 2024 - [c48]Axel Karlsson, Tianze Wang, Slawomir Nowaczyk, Sepideh Pashami, Sahar Asadi:
Mind the Data, Measuring the Performance Gap Between Tree Ensembles and Deep Learning on Tabular Data. IDA (1) 2024: 65-76 - [c47]Parisa Jamshidi, Slawomir Nowaczyk, Mahmoud Rahat:
Analysis of characteristic functions on Shapley values in Machine Learning. IE 2024: 70-77 - [c46]Parisa Jamshidi, Slawomir Nowaczyk, Mahmoud Rahat, Zahra Taghiyarrenani:
Explainable Federated Learning by Incremental Decision Trees. TempXAI@PKDD/ECML 2024: 58-69 - [e9]Slawomir Nowaczyk, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova:
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part I. Communications in Computer and Information Science 1947, Springer 2024, ISBN 978-3-031-50395-5 [contents] - [e8]Slawomir Nowaczyk, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova:
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part II. Communications in Computer and Information Science 1948, Springer 2024, ISBN 978-3-031-50484-6 [contents] - [e7]Slawomir Nowaczyk, Myra Spiliopoulou, Marco Ragni, Olga Fink:
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), Santiago de Compostela, Spain, 19 October 2024. CEUR Workshop Proceedings 3765, CEUR-WS.org 2024 [contents] - [e6]Albert Bifet, Tomas Krilavicius, Ioanna Miliou, Slawomir Nowaczyk:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IX. Lecture Notes in Computer Science 14949, Springer 2024, ISBN 978-3-031-70377-5 [contents] - [e5]Albert Bifet, Tomas Krilavicius, Ioanna Miliou, Slawomir Nowaczyk:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part X. Lecture Notes in Computer Science 14950, Springer 2024, ISBN 978-3-031-70380-5 [contents] - [i22]Mohamed Abuella, Hadi Fanaee Tork, Slawomir Nowaczyk, Simon Johansson, Ethan Faghani:
Time-Series Analysis Approach for Improving Energy Efficiency of a Fixed-Route Vessel in Short-Sea Shipping. CoRR abs/2402.00698 (2024) - [i21]Mohamed Abuella, M. Amine Atoui, Slawomir Nowaczyk, Simon Johansson, Ethan Faghani:
Spatial Clustering Approach for Vessel Path Identification. CoRR abs/2403.05778 (2024) - [i20]Mohamed Abuella, Hadi Fanaee Tork, M. Amine Atoui, Slawomir Nowaczyk, Simon Johansson, Ethan Faghani:
Data Analytics for Improving Energy Efficiency in Short Sea Shipping. CoRR abs/2404.00902 (2024) - [i19]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi, Julia Handl:
Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks. CoRR abs/2404.03992 (2024) - [i18]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi:
Fast Genetic Algorithm for feature selection - A qualitative approximation approach. CoRR abs/2404.03996 (2024) - [i17]Guojun Liang, Prayag Tiwari, Slawomir Nowaczyk, Stefan Byttner:
Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation. CoRR abs/2405.10995 (2024) - [i16]Mahmoud Rahat, Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk, Shamik Choudhury, Leo Petrin, Thorsteinn S. Rögnvaldsson, Andreas Voskou, Carlo Metta, Claudio Savelli:
Volvo Discovery Challenge at ECML-PKDD 2024. CoRR abs/2409.11446 (2024) - 2023
- [j27]Awais Ashfaq, Markus Lingman, Murat Sensoy, Slawomir Nowaczyk:
DEED: DEep Evidential Doctor. Artif. Intell. 325: 104019 (2023) - [j26]Kunru Chen, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Sepideh Pashami, Jonas Klang, Gustav Sternelöv:
Material handling machine activity recognition by context ensemble with gated recurrent units. Eng. Appl. Artif. Intell. 126: 106992 (2023) - [j25]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi:
Fast Genetic Algorithm for feature selection - A qualitative approximation approach. Expert Syst. Appl. 211: 118528 (2023) - [j24]Zahra Taghiyarrenani, Slawomir Nowaczyk, Sepideh Pashami, Mohamed-Rafik Bouguelia:
Multi-domain adaptation for regression under conditional distribution shift. Expert Syst. Appl. 224: 119907 (2023) - [j23]Alexander Galozy, Slawomir Nowaczyk:
Information-gathering in latent bandits. Knowl. Based Syst. 260: 110099 (2023) - [j22]Pablo del Moral, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Sepideh Pashami:
Pitfalls of assessing extracted hierarchies for multi-class classification. Pattern Recognit. 136: 109225 (2023) - [j21]Guojun Liang, KinTak U, Xin Ning, Prayag Tiwari, Slawomir Nowaczyk, Neeraj Kumar:
Semantics-Aware Dynamic Graph Convolutional Network for Traffic Flow Forecasting. IEEE Trans. Veh. Technol. 72(6): 7796-7809 (2023) - [c45]Parisa Jamshidi, Slawomir Nowaczyk, Mahmoud Rahat:
EcoShap: Save Computations by only Calculating Shapley Values for Relevant Features. ECAI Workshops (1) 2023: 24-42 - [c44]Szymon Bobek, Slawomir Nowaczyk, Sepideh Pashami, Zahra Taghiyarrenani, Grzegorz J. Nalepa:
Towards Explainable Deep Domain Adaptation. ECAI Workshops (1) 2023: 101-113 - [c43]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi:
Fast Genetic Algorithm for feature selection - A qualitative approximation approach. GECCO Companion 2023: 11-12 - [c42]Kunru Chen, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Sepideh Pashami, Jonas Klang, Gustav Sternelöv:
Toward Solving Domain Adaptation with Limited Source Labeled Data. ICDM (Workshops) 2023: 1240-1246 - [c41]Amirhossein Berenji, Slawomir Nowaczyk, Zahra Taghiyarrenani:
Data-Centric Perspective on Explainability Versus Performance Trade-Off. IDA 2023: 42-54 - [c40]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: 195-207 - [c39]João Gama, Slawomir Nowaczyk, Sepideh Pashami, Rita P. Ribeiro, Grzegorz J. Nalepa, Bruno Veloso:
XAI for Predictive Maintenance. KDD 2023: 5798-5799 - [c38]Mohamed Abuella, M. Amine Atoui, Slawomir Nowaczyk, Simon Johansson, Ethan Faghani:
Data-Driven Explainable Artificial Intelligence for Energy Efficiency in Short-Sea Shipping. ECML/PKDD (7) 2023: 226-241 - [c37]Szymon Bobek, Slawomir Nowaczyk, João Gama, Sepideh Pashami, Rita P. Ribeiro, Zahra Taghiyarrenani, Bruno Veloso, Lala H. Rajaoarisoa, Maciej Szelazek, Grzegorz J. Nalepa:
Why Industry 5.0 Needs XAI 2.0? xAI (Late-breaking Work, Demos, Doctoral Consortium) 2023: 1-6 - [e4]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
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. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e3]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
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. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - [i15]Guojun Liang, Prayag Tiwari, Slawomir Nowaczyk, Stefan Byttner, Fernando Alonso-Fernandez:
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting. CoRR abs/2305.09703 (2023) - [i14]Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk:
Learning Causal Mechanisms through Orthogonal Neural Networks. CoRR abs/2306.03938 (2023) - [i13]Sepideh Pashami, Slawomir Nowaczyk, Yuantao Fan, Jakub Jakubowski, Nuno Paiva, Narjes Davari, Szymon Bobek, Samaneh Jamshidi, Hamid Sarmadi, Abdallah Alabdallah, Rita P. Ribeiro, Bruno Veloso, Moamar Sayed Mouchaweh, Lala H. Rajaoarisoa, Grzegorz J. Nalepa, João Gama:
Explainable Predictive Maintenance. CoRR abs/2306.05120 (2023) - [i12]Zahra Taghiyarrenani, Abdallah Alabdallah, Slawomir Nowaczyk, Sepideh Pashami:
Heterogeneous Federated Learning via Personalized Generative Networks. CoRR abs/2308.13265 (2023) - [i11]Alexander Galozy, Sadi Alawadi, Victor R. Kebande, Slawomir Nowaczyk:
Beyond Random Noise: Insights on Anonymization Strategies from a Latent Bandit Study. CoRR abs/2310.00221 (2023) - [i10]Yuantao Fan, Zhenkan Wang, Sepideh Pashami, Slawomir Nowaczyk, Henrik Ydreskog:
Forecasting Auxiliary Energy Consumption for Electric Heavy-Duty Vehicles. CoRR abs/2311.16003 (2023) - 2022
- [j20]Pablo del Moral, Slawomir Nowaczyk, Sepideh Pashami:
Why Is Multiclass Classification Hard? IEEE Access 10: 80448-80462 (2022) - [j19]Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, Onur Dikmen:
Wisdom of the contexts: active ensemble learning for contextual anomaly detection. Data Min. Knowl. Discov. 36(6): 2410-2458 (2022) - [j18]Slawomir Nowaczyk, Andrea Resmini, Vicky Long, Vaike Fors, Martin Cooney, Eduardo K. Duarte, Sarah Pink, Eren Erdal Aksoy, Alexey V. Vinel, Mark Dougherty:
Smaller is smarter: A case for small to medium-sized smart cities. J. Smart Cities Soc. 1(2): 95-117 (2022) - [j17]Hamid Sarmadi, Slawomir Nowaczyk, Rune Prytz, Miguel A. Simão:
Attention Horizon as a Predictor for the Fuel Consumption Rate of Drivers. Sensors 22(6): 2301 (2022) - [j16]Kunru Chen, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Sepideh Pashami, Emilia Johansson, Gustav Sternelöv:
Semi-Supervised Learning for Forklift Activity Recognition from Controller Area Network (CAN) Signals. Sensors 22(11): 4170 (2022) - [c36]Narjes Davari, Sepideh Pashami, Bruno Veloso, Slawomir Nowaczyk, Yuantao Fan, Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
A Fault Detection Framework Based on LSTM Autoencoder: A Case Study for Volvo Bus Data Set. IDA 2022: 39-52 - [c35]Amirhossein Berenji, Zahra Taghiyarrenani, Slawomir Nowaczyk:
curr2vib: Modality Embedding Translation for Broken-Rotor Bar Detection. PKDD/ECML Workshops (2) 2022: 423-437 - [c34]Yuantao Fan, Hamid Sarmadi, Slawomir Nowaczyk:
Incorporating Physics-Based Models into Data Driven Approaches for Air Leak Detection in City Buses. PKDD/ECML Workshops (2) 2022: 438-450 - [c33]Zahra Taghiyarrenani, Slawomir Nowaczyk, Sepideh Pashami, Mohamed-Rafik Bouguelia:
Towards Geometry-Preserving Domain Adaptation for Fault Identification. PKDD/ECML Workshops (2) 2022: 451-460 - [c32]Samaneh Jamshidi, Slawomir Nowaczyk, Hadi Fanaee-T, Mahmoud Rahat:
A Systematic Approach for Tracking the Evolution of XAI as a Field of Research. PKDD/ECML Workshops (2) 2022: 461-476 - [c31]Enayat Rajabi, Slawomir Nowaczyk, Sepideh Pashami, Magnus Bergquist:
An Explainable Knowledge-based AI Framework for Mobility as a Service. SEKE 2022: 312-316 - [i9]Alexander Galozy, Slawomir Nowaczyk:
Information-Gathering in Latent Bandits. CoRR abs/2207.03635 (2022) - 2021
- [j15]Juhee Bae, Tove Helldin, Maria Riveiro, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, Göran Falkman:
Interactive Clustering: A Comprehensive Review. ACM Comput. Surv. 53(1): 1:1-1:39 (2021) - [j14]Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk, Sepideh Pashami:
Parallel orthogonal deep neural network. Neural Networks 140: 167-183 (2021) - [c30]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi:
Surrogate-Assisted Genetic Algorithm for Wrapper Feature Selection. CEC 2021: 776-785 - [c29]Mohammed Ghaith Altarabichi, Yuantao Fan, Sepideh Pashami, Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk:
Extracting Invariant Features for Predicting State of Health of Batteries in Hybrid Energy Buses. DSAA 2021: 1-6 - [c28]Awais Ashfaq, Markus Lingman, Slawomir Nowaczyk:
KAFE: Knowledge and Frequency Adapted Embeddings. LOD 2021: 132-146 - [i8]Pablo del Moral, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Sepideh Pashami:
Pitfalls of Assessing Extracted Hierarchies for Multi-Class Classification. CoRR abs/2101.11095 (2021) - [i7]Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, Onur Dikmen:
Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection. CoRR abs/2101.11560 (2021) - [i6]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi:
Surrogate-Assisted Genetic Algorithm for Wrapper Feature Selection. CoRR abs/2111.09074 (2021) - 2020
- [j13]Taha Khan, Lina E. Lundgren, David G. Anderson, Irena Nowak, Mark Dougherty, Antanas Verikas, Misha Pavel, Holly B. Jimison, Slawomir Nowaczyk, Vered Aharonson:
Assessing Parkinson's disease severity using speech analysis in non-native speakers. Comput. Speech Lang. 61: 101047 (2020) - [j12]Ece Calikus, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Onur Dikmen:
No free lunch but a cheaper supper: A general framework for streaming anomaly detection. Expert Syst. Appl. 155: 113453 (2020) - [j11]Alexander Galozy, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Mattias Ohlsson, Markus Lingman:
Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation. Int. J. Medical Informatics 136: 104092 (2020) - [j10]Reza Khoshkangini, Peyman Sheikholharam Mashhadi, Peter Berck, Saeed Gholami Shahbandi, Sepideh Pashami, Slawomir Nowaczyk, Tobias Niklasson:
Early Prediction of Quality Issues in Automotive Modern Industry. Inf. 11(7): 354 (2020) - [j9]Alexander Galozy, Slawomir Nowaczyk:
Prediction and pattern analysis of medication refill adherence through electronic health records and dispensation data. J. Biomed. Informatics X 6-7: 100075 (2020) - [j8]Yuantao Fan, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson:
Transfer learning for remaining useful life prediction based on consensus self-organizing models. Reliab. Eng. Syst. Saf. 203: 107098 (2020) - [c27]Oskar Dahl, Fredrik Johansson, Reza Khoshkangini, Sepideh Pashami, Slawomir Nowaczyk, Pihl Claes:
Understanding Association Between Logged Vehicle Data and Vehicle Marketing Parameters: Using Clustering and Rule-Based Machine Learning. IMMS 2020: 13-22 - [c26]Amira Soliman, Sarunas Girdzijauskas, Mohamed-Rafik Bouguelia, Sepideh Pashami, Slawomir Nowaczyk:
Decentralized and Adaptive K-Means Clustering for Non-IID Data Using HyperLogLog Counters. PAKDD (1) 2020: 343-355 - [c25]Kunru Chen, Sepideh Pashami, Slawomir Nowaczyk, Emilia Johansson, Gustav Sternelöv, Thorsteinn S. Rögnvaldsson:
Forklift Truck Activity Recognition from CAN Data. IoT Streams/ITEM@PKDD/ECML 2020: 119-126 - [i5]Alexander Galozy, Slawomir Nowaczyk, Mattias Ohlsson:
Corrupted Contextual Bandits with Action Order Constraints. CoRR abs/2011.07989 (2020)
2010 – 2019
- 2019
- [j7]Awais Ashfaq, Anita Pinheiro Sant'Anna, Markus Lingman, Slawomir Nowaczyk:
Readmission prediction using deep learning on electronic health records. J. Biomed. Informatics 97 (2019) - [c24]Alexander Galozy, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna:
Towards Understanding ICU Treatments Using Patient Health Trajectories. KR4HC/ProHealth/TEAAM@AIME 2019: 67-81 - [c23]Kunru Chen, Sepideh Pashami, Yuantao Fan, Slawomir Nowaczyk:
Predicting Air Compressor Failures Using Long Short Term Memory Networks. EPIA (1) 2019: 596-609 - [c22]Reza Khoshkangini, Sepideh Pashami, Slawomir Nowaczyk:
Warranty Claim Rate Prediction Using Logged Vehicle Data. EPIA (1) 2019: 663-674 - [c21]Ahmad Al-Shishtawy, Juhee Bae, Mohamed-Rafik Bouguelia, Göran Falkman, Sarunas Girdzijauskas, Olof Gönerup, Anders Holst, Alexander Karlsson, Slawomir Nowaczyk, Sepideh Pashami, Alan Said, Amira A. Soliman El Hosary:
Eliciting Structures in Data. IUI Workshops 2019 - [c20]Grzegorz J. Nalepa, Michal Araszkiewicz, Slawomir Nowaczyk, Szymon Bobek:
Building Trust to AI Systems Through Explainability. Technical and legal perspectives. XAILA@JURIX 2019 - [c19]Parivash Pirasteh, Slawomir Nowaczyk, Sepideh Pashami, Magnus Löwenadler, Klas Thunberg, Henrik Ydreskog, Peter Berck:
Interactive feature extraction for diagnostic trouble codes in predictive maintenance: A case study from automotive domain. IDM@WSDM 2019: 4:1-4:10 - [c18]Ece Calikus, Yuantao Fan, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna:
Interactive-COSMO: Consensus Self-Organized Models for Fault Detection with Expert Feedback. IDM@WSDM 2019: 5:1-5:9 - [e2]Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic:
Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems - AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11979, Springer 2019, ISBN 978-3-030-37445-7 [contents] - [i4]Ece Calikus, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Henrik Gadd, Sven Werner:
A Data-Driven Approach for Discovery of Heat Load Patterns in District Heating. CoRR abs/1901.04863 (2019) - [i3]Ece Calikus, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Onur Dikmen:
No Free Lunch But A Cheaper Supper: A General Framework for Streaming Anomaly Detection. CoRR abs/1909.06927 (2019) - [i2]Yuantao Fan, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson:
Transfer learning for Remaining Useful Life Prediction Based on Consensus Self-Organizing Models. CoRR abs/1909.07053 (2019) - [i1]Awais Ashfaq, Slawomir Nowaczyk:
Machine learning in healthcare - a system's perspective. CoRR abs/1909.07370 (2019) - 2018
- [j6]Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Stefan Byttner, Rune Prytz, Magnus Svensson:
Self-monitoring for maintenance of vehicle fleets. Data Min. Knowl. Discov. 32(2): 344-384 (2018) - [j5]Mohamed-Rafik Bouguelia, Slawomir Nowaczyk, Amir Hossein Payberah:
An adaptive algorithm for anomaly and novelty detection in evolving data streams. Data Min. Knowl. Discov. 32(6): 1597-1633 (2018) - [j4]Mohamed-Rafik Bouguelia, Alexander Karlsson, Sepideh Pashami, Slawomir Nowaczyk, Anders Holst:
Mode tracking using multiple data streams. Inf. Fusion 43: 33-46 (2018) - [j3]Mohamed-Rafik Bouguelia, Slawomir Nowaczyk, KC Santosh, Antanas Verikas:
Agreeing to disagree: active learning with noisy labels without crowdsourcing. Int. J. Mach. Learn. Cybern. 9(8): 1307-1319 (2018) - [j2]Evaldas Vaiciukynas, Matej Ulicny, Sepideh Pashami, Slawomir Nowaczyk:
Learning Low-Dimensional Representation of Bivariate Histogram Data. IEEE Trans. Intell. Transp. Syst. 19(11): 3723-3735 (2018) - [c17]Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Ece Calikus, Yuantao Fan:
Monitoring Equipment Operation Through Model and Event Discovery. IDEAL (2) 2018: 41-53 - [c16]Martin Cooney, Sepideh Pashami, Anita Pinheiro Sant'Anna, Yuantao Fan, Slawomir Nowaczyk:
Pitfalls of Affective Computing: How can the automatic visual communication of emotions lead to harm, and what can be done to mitigate such risks. WWW (Companion Volume) 2018: 1563-1566 - 2017
- [c15]Mohamed-Rafik Bouguelia, Sepideh Pashami, Slawomir Nowaczyk:
Multi-Task Representation Learning. SAIS 2017: 137:006 - 2016
- [c14]Tove Helldin, Maria Riveiro, Sepideh Pashami, Göran Falkman, Stefan Byttner, Slawomir Nowaczyk:
Supporting Analytical Reasoning - A Study from the Automotive Industry. HCI (5) 2016: 20-31 - [c13]Iulian Carpatorea, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson, Marcus Elmer, Johan Lodin:
Learning of Aggregate Features for Comparing Drivers Based on Naturalistic Data. ICMLA 2016: 1067-1072 - [c12]Xudong Teng, Yuantao Fan, Slawomir Nowaczyk:
Evaluation of micro-flaws in metallic material based on a self-organized data-driven approach. ICPHM 2016: 1-5 - [c11]Thorsteinn S. Rögnvaldsson, Antanas Verikas, Josef Bigün, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Björn Åstrand, Jens Lundström, Stefan Byttner, Roland Thörner, Fernando Alonso-Fernandez, Martin Cooney, Rafael Valencia:
Center for Applied Intelligent Systems Research (Position paper). SAIS 2016: 129:005 - 2015
- [j1]Rune Prytz, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson, Stefan Byttner:
Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data. Eng. Appl. Artif. Intell. 41: 139-150 (2015) - [c10]Yuantao Fan, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson:
Evaluation of Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet. INNS Conference on Big Data 2015: 447-456 - [c9]