PUBLIKATIONSSERVER

Alaa Othman

13 Publikationen

Alle markieren

[13]
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
 
[12]
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.)
 
[11]
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.)
 
[10]
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
 
[9]
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
 
[8]
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
 
[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: 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
 
[3]
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
 
[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

13 Publikationen

Alle markieren

[13]
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
 
[12]
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.)
 
[11]
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.)
 
[10]
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
 
[9]
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
 
[8]
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
 
[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: 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
 
[3]
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
 
[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