PUBLIKATIONSSERVER

Alaa Othman

15 Publikationen

Alle markieren

[15]
2026 | Konferenzbeitrag | FH-PUB-ID: 6898 | OA
B. Jaster, A. Tharwat, E. M. Sheikh, M. Kohlhase, and W. Schenck, “Low Query Budget Active Learning for Classification and Regression,” in 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, Porto, Portugal, 2026, pp. 5–21.
HSBI-PUB | DOI | Download (ext.)
 
[14]
2026 | Artikel | FH-PUB-ID: 6655 | OA
A. Tharwat, B. Jaster, W. Schenck, and M. Kohlhase, “Active learning evaluation metrics for classification and regression frameworks,” Engineering Applications of Artificial Intelligence, vol. 171, 2026.
HSBI-PUB | DOI | Download (ext.)
 
[13]
2025 | Artikel | FH-PUB-ID: 5853 | OA
M. M. Eid, K. ElDahshan, A. H. Abouali, and A. Tharwat, “Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance,” Algorithms, vol. 18, no. 3, 2025.
HSBI-PUB | DOI | Download (ext.)
 
[12]
2025 | Fachbuch | FH-PUB-ID: 5854
A. Tharwat, Python Adventures for Young Coders. Explore the World of Programming. Berkeley, CA: Apress, 2025.
HSBI-PUB | DOI
 
[11]
2024 | Artikel | FH-PUB-ID: 5495
A. Tharwat and W. Schenck, “Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget,” IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 8, pp. 4317–4330, 2024.
HSBI-PUB | DOI
 
[10]
2024 | Artikel | FH-PUB-ID: 5566
A. Tharwat and W. Schenck, “Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget,” IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 8, pp. 4317–4330, 2024.
HSBI-PUB | DOI
 
[9]
2024 | Artikel | FH-PUB-ID: 5568
A. Tharwat and W. Schenck, “Active Learning for Handling Missing Data,” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 2, pp. 3273–3287, 2024.
HSBI-PUB | DOI
 
[8]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 5570
A. Tharwat, M. Herde, M. T. Pham, and B. Sick, “Tutorial: Interactive Adaptive Learning,” presented at the 8th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Sep. 9th, 2024, Vilnius, Lithuania, Vilnius, Lithuania, 2024.
HSBI-PUB | Download (ext.)
 
[7]
2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 5569
A. Tharwat, M. Bunse, B. Hammer, G. Krempl, V. Lemaire, and Saadallah Amal, “Tutorial: Interactive Adaptive Learning.,” presented at the 7th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Torino, Italy, 2023.
HSBI-PUB | Download (ext.)
 
[6]
2023 | Artikel | FH-PUB-ID: 2774 | OA
A. Tharwat and W. Schenck, “A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions,” Mathematics, vol. 11, no. 4, 2023.
HSBI-PUB | DOI | Download (ext.)
 
[5]
2022 | Artikel | FH-PUB-ID: 2775 | OA
A. Tharwat and W. Schenck, “A Novel Low-Query-Budget Active Learner with Pseudo-Labels for Imbalanced Data,” Mathematics, vol. 10, no. 7, 2022.
HSBI-PUB | DOI | Download (ext.)
 
[4]
2021 | Artikel | FH-PUB-ID: 2777
A. Tharwat and W. Schenck, “Population initialization techniques for evolutionary algorithms for single-objective constrained optimization problems: Deterministic vs. stochastic techniques,” Swarm and Evolutionary Computation, vol. 67, 2021.
HSBI-PUB | DOI
 
[3]
2021 | Artikel | FH-PUB-ID: 1202
A. Tharwat and W. Schenck, “A conceptual and practical comparison of PSO-style optimization algorithms,” Expert Systems with Applications, vol. 167, 2021.
HSBI-PUB | DOI
 
[2]
2020 | Artikel | FH-PUB-ID: 1204
A. Tharwat and W. Schenck, “Balancing Exploration and Exploitation: A novel active learner for imbalanced data,” Knowledge-Based Systems, vol. 210, 2020.
HSBI-PUB | DOI
 
[1]
2020 | Konferenzbeitrag | FH-PUB-ID: 1206
D. Pelkmann, A. Tharwat, and W. Schenck, “How to Label? Combining Experts’ Knowledge for German Text Classification,” in 2020 7th Swiss Conference on Data Science (SDS), Luzern, Switzerland, 2020, pp. 61–62.
HSBI-PUB | DOI
 
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15 Publikationen

Alle markieren

[15]
2026 | Konferenzbeitrag | FH-PUB-ID: 6898 | OA
B. Jaster, A. Tharwat, E. M. Sheikh, M. Kohlhase, and W. Schenck, “Low Query Budget Active Learning for Classification and Regression,” in 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, Porto, Portugal, 2026, pp. 5–21.
HSBI-PUB | DOI | Download (ext.)
 
[14]
2026 | Artikel | FH-PUB-ID: 6655 | OA
A. Tharwat, B. Jaster, W. Schenck, and M. Kohlhase, “Active learning evaluation metrics for classification and regression frameworks,” Engineering Applications of Artificial Intelligence, vol. 171, 2026.
HSBI-PUB | DOI | Download (ext.)
 
[13]
2025 | Artikel | FH-PUB-ID: 5853 | OA
M. M. Eid, K. ElDahshan, A. H. Abouali, and A. Tharwat, “Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance,” Algorithms, vol. 18, no. 3, 2025.
HSBI-PUB | DOI | Download (ext.)
 
[12]
2025 | Fachbuch | FH-PUB-ID: 5854
A. Tharwat, Python Adventures for Young Coders. Explore the World of Programming. Berkeley, CA: Apress, 2025.
HSBI-PUB | DOI
 
[11]
2024 | Artikel | FH-PUB-ID: 5495
A. Tharwat and W. Schenck, “Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget,” IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 8, pp. 4317–4330, 2024.
HSBI-PUB | DOI
 
[10]
2024 | Artikel | FH-PUB-ID: 5566
A. Tharwat and W. Schenck, “Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget,” IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 8, pp. 4317–4330, 2024.
HSBI-PUB | DOI
 
[9]
2024 | Artikel | FH-PUB-ID: 5568
A. Tharwat and W. Schenck, “Active Learning for Handling Missing Data,” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 2, pp. 3273–3287, 2024.
HSBI-PUB | DOI
 
[8]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 5570
A. Tharwat, M. Herde, M. T. Pham, and B. Sick, “Tutorial: Interactive Adaptive Learning,” presented at the 8th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Sep. 9th, 2024, Vilnius, Lithuania, Vilnius, Lithuania, 2024.
HSBI-PUB | Download (ext.)
 
[7]
2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 5569
A. Tharwat, M. Bunse, B. Hammer, G. Krempl, V. Lemaire, and Saadallah Amal, “Tutorial: Interactive Adaptive Learning.,” presented at the 7th Intl. Worksh. & Tutorial on Interactive Adaptive Learning, Torino, Italy, 2023.
HSBI-PUB | Download (ext.)
 
[6]
2023 | Artikel | FH-PUB-ID: 2774 | OA
A. Tharwat and W. Schenck, “A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions,” Mathematics, vol. 11, no. 4, 2023.
HSBI-PUB | DOI | Download (ext.)
 
[5]
2022 | Artikel | FH-PUB-ID: 2775 | OA
A. Tharwat and W. Schenck, “A Novel Low-Query-Budget Active Learner with Pseudo-Labels for Imbalanced Data,” Mathematics, vol. 10, no. 7, 2022.
HSBI-PUB | DOI | Download (ext.)
 
[4]
2021 | Artikel | FH-PUB-ID: 2777
A. Tharwat and W. Schenck, “Population initialization techniques for evolutionary algorithms for single-objective constrained optimization problems: Deterministic vs. stochastic techniques,” Swarm and Evolutionary Computation, vol. 67, 2021.
HSBI-PUB | DOI
 
[3]
2021 | Artikel | FH-PUB-ID: 1202
A. Tharwat and W. Schenck, “A conceptual and practical comparison of PSO-style optimization algorithms,” Expert Systems with Applications, vol. 167, 2021.
HSBI-PUB | DOI
 
[2]
2020 | Artikel | FH-PUB-ID: 1204
A. Tharwat and W. Schenck, “Balancing Exploration and Exploitation: A novel active learner for imbalanced data,” Knowledge-Based Systems, vol. 210, 2020.
HSBI-PUB | DOI
 
[1]
2020 | Konferenzbeitrag | FH-PUB-ID: 1206
D. Pelkmann, A. Tharwat, and W. Schenck, “How to Label? Combining Experts’ Knowledge for German Text Classification,” in 2020 7th Swiss Conference on Data Science (SDS), Luzern, Switzerland, 2020, pp. 61–62.
HSBI-PUB | DOI
 
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Zitationsstil: IEEE

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