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ORCIDSepideh Pashami
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2020 – today
- 2024
[j14]Abdallah Alabdallah
, Mattias Ohlsson, Sepideh Pashami, Thorsteinn S. Rögnvaldsson:
The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models. Artif. Intell. Medicine 148: 102781 (2024)- [j13]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) - [c34]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 - [c33]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 - [c32]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 - [c31]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 - [c30]Abdallah Alabdallah, Jakub Jakubowski, Sepideh Pashami, Szymon Bobek, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson, Grzegorz J. Nalepa:
Understanding Survival Models Through Counterfactual Explanations. ICCS (4) 2024: 310-324 - [c29]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 - [i14]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) - [i13]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) - [i12]Jakub Jakubowski, Natalia Wojak-Strzelecka, Rita P. Ribeiro, Sepideh Pashami, Szymon Bobek, João Gama, Grzegorz J. Nalepa:
Artificial Intelligence Approaches for Predictive Maintenance in the Steel Industry: A Survey. CoRR abs/2405.12785 (2024) - [i11]Abdallah Alabdallah, Omar Hamed, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson, Sepideh Pashami:
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis. CoRR abs/2407.13849 (2024) - 2023
- [j12]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) - [j11]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) - [j10]Zahra Taghiyarrenani, Slawomir Nowaczyk, Sepideh Pashami, Mohamed-Rafik Bouguelia:
Multi-domain adaptation for regression under conditional distribution shift. Expert Syst. Appl. 224: 119907 (2023) - [j9]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) - [c28]Szymon Bobek, Slawomir Nowaczyk, Sepideh Pashami, Zahra Taghiyarrenani, Grzegorz J. Nalepa:
Towards Explainable Deep Domain Adaptation. ECAI Workshops (1) 2023: 101-113 - [c27]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 - [c26]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 - [c25]Jia Fu, Jiarui Tan, Wenjie Yin, Sepideh Pashami, Mårten Björkman:
Component attention network for multimodal dance improvisation recognition. ICMI 2023: 114-118 - [c24]João Gama, Slawomir Nowaczyk, Sepideh Pashami, Rita P. Ribeiro, Grzegorz J. Nalepa, Bruno Veloso:
XAI for Predictive Maintenance. KDD 2023: 5798-5799 - [c23]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 - [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 A. D. 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] - [e2]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 A. D. 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] - [i10]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) - [i9]Zahra Taghiyarrenani, Abdallah Alabdallah, Slawomir Nowaczyk, Sepideh Pashami:
Heterogeneous Federated Learning via Personalized Generative Networks. CoRR abs/2308.13265 (2023) - [i8]Jia Fu, Jiarui Tan, Wenjie Yin, Sepideh Pashami, Mårten Björkman:
Component attention network for multimodal dance improvisation recognition. CoRR abs/2310.05938 (2023) - [i7]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
- [j8]Pablo del Moral, Slawomir Nowaczyk, Sepideh Pashami:
Why Is Multiclass Classification Hard? IEEE Access 10: 80448-80462 (2022) - [j7]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) - [c22]Abdallah Alabdallah, Sepideh Pashami, Thorsteinn S. Rögnvaldsson, Mattias Ohlsson:
SurvSHAP: A Proxy-Based Algorithm for Explaining Survival Models with SHAP. DSAA 2022: 1-10 - [c21]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 - [c20]Zahra Taghiyarrenani, Slawomir Nowaczyk, Sepideh Pashami, Mohamed-Rafik Bouguelia:
Towards Geometry-Preserving Domain Adaptation for Fault Identification. PKDD/ECML Workshops (2) 2022: 451-460 - [c19]Francisco J. Peña, Angel Luis Gonzalez, Sepideh Pashami, Ahmad Al-Shishtawy, Amir Hossein Payberah:
Siambert: Siamese Bert-based Code Search. SAIS 2022: 1-7 - [c18]Enayat Rajabi, Slawomir Nowaczyk, Sepideh Pashami, Magnus Bergquist:
An Explainable Knowledge-based AI Framework for Mobility as a Service. SEKE 2022: 312-316 - [i6]Abdallah Alabdallah, Mattias Ohlsson, Sepideh Pashami, Thorsteinn S. Rögnvaldsson:
The Concordance Index decomposition: a measure for a deeper understanding of survival prediction models. CoRR abs/2203.00144 (2022) - 2021
- [j6]Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk, Sepideh Pashami:
Parallel orthogonal deep neural network. Neural Networks 140: 167-183 (2021) - [c17]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi:
Surrogate-Assisted Genetic Algorithm for Wrapper Feature Selection. CEC 2021: 776-785 - [c16]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 - [c15]Marcus Hägglund, Francisco J. Peña, Sepideh Pashami, Ahmad Al-Shishtawy, Amir Hossein Payberah:
COCLUBERT: Clustering Machine Learning Source Code. ICMLA 2021: 151-158 - [i5]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) - [i4]Cristofer Englund, Eren Erdal Aksoy, Fernando Alonso-Fernandez, Martin Daniel Cooney, Sepideh Pashami, Björn Åstrand:
AI in Smart Cities: Challenges and approaches to enable road vehicle automation and smart traffic control. CoRR abs/2104.03150 (2021) - [i3]Mohammed Ghaith Altarabichi, Slawomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi:
Surrogate-Assisted Genetic Algorithm for Wrapper Feature Selection. CoRR abs/2111.09074 (2021) - 2020
- [j5]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) - [c14]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 - [c13]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 - [c12]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 - [e1]João Gama, Sepideh Pashami, Albert Bifet, Moamar Sayed Mouchaweh, Holger Fröning, Franz Pernkopf, Gregor Schiele, Michaela Blott:
IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning - Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers. Communications in Computer and Information Science 1325, Springer 2020, ISBN 978-3-030-66769-6 [contents] - [i2]Martin Cooney, Sepideh Pashami, Eric Järpe, Awais Ashfaq:
Avoiding Improper Treatment of Persons with Dementia by Care Robots. CoRR abs/2005.06622 (2020)
2010 – 2019
- 2019
- [c11]Kunru Chen, Sepideh Pashami, Yuantao Fan, Slawomir Nowaczyk:
Predicting Air Compressor Failures Using Long Short Term Memory Networks. EPIA (1) 2019: 596-609 - [c10]Reza Khoshkangini, Sepideh Pashami, Slawomir Nowaczyk:
Warranty Claim Rate Prediction Using Logged Vehicle Data. EPIA (1) 2019: 663-674 - [c9]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 - [c8]Anders Holst, Sepideh Pashami, Juhee Bae:
Incremental Causal Discovery and Visualization. IDM@WSDM 2019: 3:1-3:6 - [c7]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 - [c6]Alan Said, Denis Parra, Juhee Bae, Sepideh Pashami:
IDM-WSDM 2019: Workshop on Interactive Data Mining. WSDM 2019: 846-847 - 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]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) - [c5]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
- [c4]Mohamed-Rafik Bouguelia, Sepideh Pashami, Slawomir Nowaczyk:
Multi-Task Representation Learning. SAIS 2017: 137:006 - [i1]Martin Cooney, Sepideh Pashami, Yuantao Fan, Anita Pinheiro Sant'Anna, Yinrong Ma, Tianyi Zhang, Yuwei Zhao, Wolfgang Hotze, Jeremy Heyne, Cristofer Englund, Achim J. Lilienthal, Tom Ziemke:
Exploring home robot capabilities by medium fidelity prototyping. CoRR abs/1710.01541 (2017) - 2016
- [c3]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 - 2015
- [b1]Sepideh Pashami:
Change detection in metal oxide gas sensor signals for open sampling systems. Örebro University, Sweden, 2015 - 2013
- [j2]Sepideh Pashami, Achim J. Lilienthal, Erik Schaffernicht, Marco Trincavelli:
TREFEX: Trend Estimation and Change Detection in the Response of MOX Gas Sensors. Sensors 13(6): 7323-7344 (2013) - 2012
- [j1]Sepideh Pashami, Achim J. Lilienthal, Marco Trincavelli:
Detecting Changes of a Distant Gas Source with an Array of MOX Gas Sensors. Sensors 12(12): 16404-16419 (2012) - 2011
- [c2]Sahar Asadi, Costin Badica, Tina Comes, Claudine Conrado, Vanessa Evers, Frans C. A. Groen, Sorin Ilie, Jan Steen Jensen, Achim J. Lilienthal, Bianca Milan, Thomas Neidhart, Kees Nieuwenhuis, Sepideh Pashami, Gregor Pavlin, Jan Pehrsson, Rani Pinchuk, Mihnea Scafes, Leo Schou-Jensen, Frank Schultmann, Niek J. E. Wijngaards:
ICT solutions supporting collaborative information acquisition, situation assessment and decision making in contemporary environmental management problems: the DIADEM approach. EnviroInfo 2011: 920-931
2000 – 2009
- 2005
- [c1]HesamAddin Dashti, Nima Aghaeepour, Sahar Asadi, Meysam Bastani, Zahra Delafkar, Fatemeh Miri Disfani, Serveh Ghaderi, Shahin Kamali, Sepideh Pashami, Alireza Siahpirani:
Dynamic Positioning Based on Voronoi Cells (DPVC). RoboCup 2005: 219-229
Coauthor Index
Peyman Sheikholharam
aka: Peyman Sheikholharam Mashhadi
aka: Peyman Sheikholharam Mashhadi
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