| Do we really need deep learning models for time series forecasting? S Elsayed, D Thyssens, A Rashed, HS Jomaa, L Schmidt-Thieme arXiv preprint arXiv:2101.02118, 2021 | 124 | 2021 |
| Hyp-rl: Hyperparameter optimization by reinforcement learning HS Jomaa, J Grabocka, L Schmidt-Thieme arXiv preprint arXiv:1906.11527, 2019 | 67 | 2019 |
| Dataset2vec: Learning dataset meta-features HS Jomaa, L Schmidt-Thieme, J Grabocka Data Mining and Knowledge Discovery 35 (3), 964-985, 2021 | 62 | 2021 |
| Hpo-b: A large-scale reproducible benchmark for black-box hpo based on openml SP Arango, HS Jomaa, M Wistuba, J Grabocka arXiv preprint arXiv:2106.06257, 2021 | 39* | 2021 |
| A computationally efficient multi-modal classification approach of disaster-related Twitter images Y Rizk, HS Jomaa, M Awad, C Castillo Proceedings of the 34th ACM/SIGAPP symposium on applied computing, 2050-2059, 2019 | 34 | 2019 |
| Handwritten amharic character recognition using a convolutional neural network MS Gondere, L Schmidt-Thieme, AS Boltena, HS Jomaa arXiv preprint arXiv:1909.12943, 2019 | 17 | 2019 |
| KerMinSVM for imbalanced datasets with a case study on arabic comics classification A Nayal, H Jomaa, M Awad Engineering Applications of Artificial Intelligence 59, 159-169, 2017 | 11 | 2017 |
| Transfer NAS with meta-learned bayesian surrogates G Shala, T Elsken, F Hutter, J Grabocka The Eleventh International Conference on Learning Representations, 2022 | 10 | 2022 |
| A hybrid convolutional approach for parking availability prediction HS Jomaa, J Grabocka, L Schmidt-Thieme, A Borek 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 8 | 2019 |
| Semantic and visual cues for humanitarian computing of natural disaster damage images HS Jomaa, Y Rizk, M Awad 2016 12th International Conference on Signal-Image Technology & Internet …, 2016 | 8 | 2016 |
| Zero-shot automl with pretrained models E Öztürk, F Ferreira, H Jomaa, L Schmidt-Thieme, J Grabocka, F Hutter International Conference on Machine Learning, 17138-17155, 2022 | 7 | 2022 |
| Multi-task learning curve forecasting across hyperparameter configurations and datasets S Jawed, H Jomaa, L Schmidt-Thieme, J Grabocka Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 6 | 2021 |
| Transfer learning for bayesian hpo with end-to-end landmark meta-features HS Jomaa, SP Arango, L Schmidt-Thieme, J Grabocka Fifth Workshop on Meta-Learning at the Conference on Neural Information …, 2021 | 5 | 2021 |
| Hyperparameter optimization with differentiable metafeatures HS Jomaa, L Schmidt-Thieme, J Grabocka arXiv preprint arXiv:2102.03776, 2021 | 5 | 2021 |
| Do we really need deep learning models for time series forecasting?, 2021 S Elsayed, D Thyssens, A Rashed, HS Jomaa, L Schmidt-Thieme URL https://arxiv. org/abs/2101 2118, 2021 | 5 | 2021 |
| Panel tracking for the extraction and the classification of speech balloons HS Jomaa, M Awad, L Ghaibeh Image Analysis and Processing—ICIAP 2015: 18th International Conference …, 2015 | 4 | 2015 |
| Balancing a two-wheeled mobile robot using adaptive control H Al-Jlailaty, H Jomaa, N Daher, D Asmar 2018 IEEE International Multidisciplinary Conference on Engineering …, 2018 | 3 | 2018 |
| Exploring the influence of data aggregation in parking prediction S Elsayed, D Thyssens, S Chamurally, A Tariq, HS Jomaa Database and Expert Systems Applications: DEXA 2020 International Workshops …, 2020 | 1 | 2020 |
| Affective Relationship between Color and Text in Arabic Comic Books HS Jomaa, M Kamereddine, A Nayal, Y Rizk, M Awad 2016 12th International Conference on Signal-Image Technology & Internet …, 2016 | 1 | 2016 |
| Transfer Learning for Automated Machine Learning: Meta-feature Learning, Black-box Hyperparameter Optimization and Applications HS Jomaa Stiftung Universität Hildesheim, 2023 | | 2023 |
Lars Schmidt-ThiemeUniversity of Hildesheim, GermanyVerified email at ismll.uni-hildesheim.de
