PUBLIKATIONSSERVER

Alaa Othman

15 Publikationen

Alle markieren

[15]
2026 | Konferenzbeitrag | FH-PUB-ID: 6898 | OA
Jaster, B., Tharwat, A., Sheikh, E. M., Kohlhase, M., & Schenck, W. (2026). Low Query Budget Active Learning for Classification and Regression. In I. Koprinska, J. Mendes-Moreira, & P. Branco (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases. International Workshops of ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Revised Selected Papers, Part IV (pp. 5–21). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-19105-2_1
HSBI-PUB | DOI | Download (ext.)
 
[14]
2026 | Artikel | FH-PUB-ID: 6655 | OA
Tharwat, A., Jaster, B., Schenck, W., & Kohlhase, M. (2026). Active learning evaluation metrics for classification and regression frameworks. Engineering Applications of Artificial Intelligence, 171. https://doi.org/10.1016/j.engappai.2026.114295
HSBI-PUB | DOI | Download (ext.)
 
[13]
2025 | Artikel | FH-PUB-ID: 5853 | OA
Eid, M. M., ElDahshan, K., Abouali, A. H., & Tharwat, A. (2025). Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance. Algorithms, 18(3). https://doi.org/10.3390/a18030119
HSBI-PUB | DOI | Download (ext.)
 
[12]
2025 | Fachbuch | FH-PUB-ID: 5854
Tharwat, A. (2025). Python Adventures for Young Coders. Explore the World of Programming. Berkeley, CA: Apress. https://doi.org/10.1007/979-8-8688-1067-1
HSBI-PUB | DOI
 
[11]
2024 | Artikel | FH-PUB-ID: 5495
Tharwat, A., & Schenck, W. (2024). Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget. IEEE Transactions on Knowledge and Data Engineering, 36(8), 4317–4330. https://doi.org/10.1109/TKDE.2024.3365189
HSBI-PUB | DOI
 
[10]
2024 | Artikel | FH-PUB-ID: 5566
Tharwat, A., & Schenck, W. (2024). Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget. IEEE Transactions on Knowledge and Data Engineering, 36(8), 4317–4330. https://doi.org/10.1109/TKDE.2024.3365189
HSBI-PUB | DOI
 
[9]
2024 | Artikel | FH-PUB-ID: 5568
Tharwat, A., & Schenck, W. (2024). Active Learning for Handling Missing Data. IEEE Transactions on Neural Networks and Learning Systems, 36(2), 3273–3287. https://doi.org/10.1109/TNNLS.2024.3352279
HSBI-PUB | DOI
 
[8]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 5570
Tharwat, A., Herde, M., Pham, M. T., & Sick, B. (2024). Tutorial: Interactive Adaptive Learning. Presented at the 8th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Sep. 9th, 2024, Vilnius, Lithuania, Vilnius, Lithuania.
HSBI-PUB | Download (ext.)
 
[7]
2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 5569
Tharwat, A., Bunse, M., Hammer, B., Krempl, G., Lemaire, V., & Amal, Saadallah. (2023). Tutorial: Interactive Adaptive Learning. Presented at the 7th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Torino, Italy.
HSBI-PUB | Download (ext.)
 
[6]
2023 | Artikel | FH-PUB-ID: 2774 | OA
Tharwat, A., & Schenck, W. (2023). A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions. Mathematics, 11(4). https://doi.org/10.3390/math11040820
HSBI-PUB | DOI | Download (ext.)
 
[5]
2022 | Artikel | FH-PUB-ID: 2775 | OA
Tharwat, A., & Schenck, W. (2022). A Novel Low-Query-Budget Active Learner with Pseudo-Labels for Imbalanced Data. Mathematics, 10(7). https://doi.org/10.3390/math10071068
HSBI-PUB | DOI | Download (ext.)
 
[4]
2021 | Artikel | FH-PUB-ID: 2777
Tharwat, A., & Schenck, W. (2021). Population initialization techniques for evolutionary algorithms for single-objective constrained optimization problems: Deterministic vs. stochastic techniques. Swarm and Evolutionary Computation, 67. https://doi.org/10.1016/j.swevo.2021.100952
HSBI-PUB | DOI
 
[3]
2021 | Artikel | FH-PUB-ID: 1202
Tharwat, A., & Schenck, W. (2021). A conceptual and practical comparison of PSO-style optimization algorithms. Expert Systems with Applications, 167. https://doi.org/10.1016/j.eswa.2020.114430
HSBI-PUB | DOI
 
[2]
2020 | Artikel | FH-PUB-ID: 1204
Tharwat, A., & Schenck, W. (2020). Balancing Exploration and Exploitation: A novel active learner for imbalanced data. Knowledge-Based Systems, 210. https://doi.org/10.1016/j.knosys.2020.106500
HSBI-PUB | DOI
 
[1]
2020 | Konferenzbeitrag | FH-PUB-ID: 1206
Pelkmann, D., Tharwat, A., & Schenck, W. (2020). How to Label? Combining Experts’ Knowledge for German Text Classification. In 2020 7th Swiss Conference on Data Science (SDS) (pp. 61–62). Luzern, Switzerland: IEEE. https://doi.org/10.1109/SDS49233.2020.00023
HSBI-PUB | DOI
 
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15 Publikationen

Alle markieren

[15]
2026 | Konferenzbeitrag | FH-PUB-ID: 6898 | OA
Jaster, B., Tharwat, A., Sheikh, E. M., Kohlhase, M., & Schenck, W. (2026). Low Query Budget Active Learning for Classification and Regression. In I. Koprinska, J. Mendes-Moreira, & P. Branco (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases. International Workshops of ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Revised Selected Papers, Part IV (pp. 5–21). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-19105-2_1
HSBI-PUB | DOI | Download (ext.)
 
[14]
2026 | Artikel | FH-PUB-ID: 6655 | OA
Tharwat, A., Jaster, B., Schenck, W., & Kohlhase, M. (2026). Active learning evaluation metrics for classification and regression frameworks. Engineering Applications of Artificial Intelligence, 171. https://doi.org/10.1016/j.engappai.2026.114295
HSBI-PUB | DOI | Download (ext.)
 
[13]
2025 | Artikel | FH-PUB-ID: 5853 | OA
Eid, M. M., ElDahshan, K., Abouali, A. H., & Tharwat, A. (2025). Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance. Algorithms, 18(3). https://doi.org/10.3390/a18030119
HSBI-PUB | DOI | Download (ext.)
 
[12]
2025 | Fachbuch | FH-PUB-ID: 5854
Tharwat, A. (2025). Python Adventures for Young Coders. Explore the World of Programming. Berkeley, CA: Apress. https://doi.org/10.1007/979-8-8688-1067-1
HSBI-PUB | DOI
 
[11]
2024 | Artikel | FH-PUB-ID: 5495
Tharwat, A., & Schenck, W. (2024). Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget. IEEE Transactions on Knowledge and Data Engineering, 36(8), 4317–4330. https://doi.org/10.1109/TKDE.2024.3365189
HSBI-PUB | DOI
 
[10]
2024 | Artikel | FH-PUB-ID: 5566
Tharwat, A., & Schenck, W. (2024). Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget. IEEE Transactions on Knowledge and Data Engineering, 36(8), 4317–4330. https://doi.org/10.1109/TKDE.2024.3365189
HSBI-PUB | DOI
 
[9]
2024 | Artikel | FH-PUB-ID: 5568
Tharwat, A., & Schenck, W. (2024). Active Learning for Handling Missing Data. IEEE Transactions on Neural Networks and Learning Systems, 36(2), 3273–3287. https://doi.org/10.1109/TNNLS.2024.3352279
HSBI-PUB | DOI
 
[8]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 5570
Tharwat, A., Herde, M., Pham, M. T., & Sick, B. (2024). Tutorial: Interactive Adaptive Learning. Presented at the 8th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Sep. 9th, 2024, Vilnius, Lithuania, Vilnius, Lithuania.
HSBI-PUB | Download (ext.)
 
[7]
2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 5569
Tharwat, A., Bunse, M., Hammer, B., Krempl, G., Lemaire, V., & Amal, Saadallah. (2023). Tutorial: Interactive Adaptive Learning. Presented at the 7th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Torino, Italy.
HSBI-PUB | Download (ext.)
 
[6]
2023 | Artikel | FH-PUB-ID: 2774 | OA
Tharwat, A., & Schenck, W. (2023). A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions. Mathematics, 11(4). https://doi.org/10.3390/math11040820
HSBI-PUB | DOI | Download (ext.)
 
[5]
2022 | Artikel | FH-PUB-ID: 2775 | OA
Tharwat, A., & Schenck, W. (2022). A Novel Low-Query-Budget Active Learner with Pseudo-Labels for Imbalanced Data. Mathematics, 10(7). https://doi.org/10.3390/math10071068
HSBI-PUB | DOI | Download (ext.)
 
[4]
2021 | Artikel | FH-PUB-ID: 2777
Tharwat, A., & Schenck, W. (2021). Population initialization techniques for evolutionary algorithms for single-objective constrained optimization problems: Deterministic vs. stochastic techniques. Swarm and Evolutionary Computation, 67. https://doi.org/10.1016/j.swevo.2021.100952
HSBI-PUB | DOI
 
[3]
2021 | Artikel | FH-PUB-ID: 1202
Tharwat, A., & Schenck, W. (2021). A conceptual and practical comparison of PSO-style optimization algorithms. Expert Systems with Applications, 167. https://doi.org/10.1016/j.eswa.2020.114430
HSBI-PUB | DOI
 
[2]
2020 | Artikel | FH-PUB-ID: 1204
Tharwat, A., & Schenck, W. (2020). Balancing Exploration and Exploitation: A novel active learner for imbalanced data. Knowledge-Based Systems, 210. https://doi.org/10.1016/j.knosys.2020.106500
HSBI-PUB | DOI
 
[1]
2020 | Konferenzbeitrag | FH-PUB-ID: 1206
Pelkmann, D., Tharwat, A., & Schenck, W. (2020). How to Label? Combining Experts’ Knowledge for German Text Classification. In 2020 7th Swiss Conference on Data Science (SDS) (pp. 61–62). Luzern, Switzerland: IEEE. https://doi.org/10.1109/SDS49233.2020.00023
HSBI-PUB | DOI
 
Markierte Publikation(en)

Suche

Publikationen filtern

Darstellung / Sortierung

Zitationsstil: APA

Export / Einbettung