Music Composition Using Combination of Genetic Algorithms and Recurrent Neural Networks. - Peyman Sheikholharam; Mohammad Teshnehlab (HIS, 2008)

Boosted Test-FDA: a transductive boosting method. - Peyman Sheikholharam Mashhadi (Pattern Anal. Appl., 2019)

Resource allocation mechanisms in cloud computing: a systematic literature review. - Mostafa Vakili Fard; Amir Sahafi; Amir Masoud Rahmani; Peyman Sheikholharam Mashhadi (IET Softw., 2020)

Early Prediction of Quality Issues in Automotive Modern Industry. - Reza Khoshkangini; Peyman Sheikholharam Mashhadi; Peter Berck; Saeed Gholami Shahbandi; Sepideh Pashami; Slawomir Nowaczyk; Tobias Niklasson (Inf., 2020)

Surrogate-Assisted Genetic Algorithm for Wrapper Feature Selection. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi (CEC, 2021)

Extracting Invariant Features for Predicting State of Health of Batteries in Hybrid Energy Buses. - Mohammed Ghaith Altarabichi; Yuantao Fan; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk (DSAA, 2021)

Predicting hybrid vehicles' fuel and electric consumption using multitask learning. - Venkata Sai Vivek Uddagiri; Shankara Narayanan Bangalore Ramalingam; Mahmoud Rahat; Peyman Sheikholharam Mashhadi (DSAA, 2021)

Parallel orthogonal deep neural network. - Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk; Sepideh Pashami (Neural Networks, 2021)

Optimal Task Grouping Approach in Multitask Learning. - Reza Khoshkangini; Mohsen Tajgardan; Peyman Sheikholharam Mashhadi; Thorsteinn S. Rögnvaldsson; Daniel Tegnered (ICONIP (6), 2023)

AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, a Framework Based on Active Learning and Transfer Learning. - Zahra Kharazian; Mahmoud Rahat; Fábio F. Gama; Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk; Tony Lindgren; Sindri Magnússon (IDA, 2023)

Learning Causal Mechanisms through Orthogonal Neural Networks. - Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk (CoRR, 2023)

Fast Genetic Algorithm for feature selection - A qualitative approximation approach. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi (Expert Syst. Appl., 2023)

Predicting Vehicle Behavior Using Multi-task Ensemble Learning. - Reza Khoshkangini; Peyman Sheikholharam Mashhadi; Daniel Tegnered; Jens Lundström; Thorsteinn S. Rögnvaldsson (Expert Syst. Appl., 2023)

A Review of Randomness Techniques in Deep Neural Networks. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Julia Handl (GECCO Companion, 2024)

Invariant Feature Selection for Battery State of Health Estimation in Heterogeneous Hybrid Electric Bus Fleets. - Yuantao Fan; Mohammed Ghaith Altarabichi; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk (HAII5.0@ECAI, 2024)

Steered Metaheuristic Optimization Approach for Vehicle Breakdown Prediction. - Mohsen Tajgardan; Reza Khoshkangini; Peyman Mashhadi (ICISDM, 2024)

Expected Grad-CAM: Towards gradient faithfulness. - Vincenzo Buono; Peyman Sheikholharam Mashhadi; Mahmoud Rahat; Prayag Tiwari; Stefan Byttner (CoRR, 2024)

Volvo Discovery Challenge at ECML-PKDD 2024. - Mahmoud Rahat; Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk; Shamik Choudhury; Leo Petrin; Thorsteinn S. Rögnvaldsson; Andreas Voskou; Carlo Metta; Claudio Savelli (CoRR, 2024)

Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Julia Handl (Inf. Sci., 2024)