5 Publications
2026 | Conference Paper | LibreCat-ID: 67307 | 
Hotegni, Sedjro Salomon, and Sebastian Peitz. “SPREAD: Sampling-Based Pareto Front Refinement via Efficient Adaptive Diffusion.” In 14th International Conference on Learning Representations (ICLR), 2026. https://doi.org/10.48550/arXiv.2509.21058.
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2026 | Conference Paper | LibreCat-ID: 67300
Hotegni, Sedjro Salomon, and Sebastian Peitz. “Enhancing Adversarial Robustness Through Multi-Objective Representation Learning.” In Artificial Neural Networks and Machine Learning – ICANN 2025, edited by Walter Senn, Marcello Sanguineti, Ausra Saudargiene, Igor V. Tetko, Alessandro E. P. Villa, Viktor Jirsa, and Yoshua Bengio, 442–454. Cham: Springer Nature Switzerland, 2026. https://doi.org/10.1007/978-3-032-04558-4_35.
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2025 | Journal Article | LibreCat-ID: 67316
Peitz, Sebastian, and Sedjro Salomon Hotegni. “Multi-Objective Deep Learning: Taxonomy and Survey of the State of the Art.” Machine Learning with Applications, no. 100700 (2025). https://doi.org/10.1016/j.mlwa.2025.100700.
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2024 | Conference Paper | LibreCat-ID: 46649 |
Hotegni, Sedjro Salomon, Manuel Bastian Berkemeier, and Sebastian Peitz. “Multi-Objective Optimization for Sparse Deep Multi-Task Learning.” In 2024 International Joint Conference on Neural Networks (IJCNN), 9. Yokohama, Japan: IEEE, 2024. https://doi.org/10.1109/IJCNN60899.2024.10650994.
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2023 | Conference Paper | LibreCat-ID: 45695 |
Hotegni, Sedjro Salomon, Sepideh Mahabadi, and Ali Vakilian. “Approximation Algorithms for Fair Range Clustering.” In Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023., n.d.
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5 Publications
2026 | Conference Paper | LibreCat-ID: 67307 |
Hotegni, Sedjro Salomon, and Sebastian Peitz. “SPREAD: Sampling-Based Pareto Front Refinement via Efficient Adaptive Diffusion.” In 14th International Conference on Learning Representations (ICLR), 2026. https://doi.org/10.48550/arXiv.2509.21058.
LibreCat
| DOI
| Download (ext.)
2026 | Conference Paper | LibreCat-ID: 67300
Hotegni, Sedjro Salomon, and Sebastian Peitz. “Enhancing Adversarial Robustness Through Multi-Objective Representation Learning.” In Artificial Neural Networks and Machine Learning – ICANN 2025, edited by Walter Senn, Marcello Sanguineti, Ausra Saudargiene, Igor V. Tetko, Alessandro E. P. Villa, Viktor Jirsa, and Yoshua Bengio, 442–454. Cham: Springer Nature Switzerland, 2026. https://doi.org/10.1007/978-3-032-04558-4_35.
LibreCat
| DOI
2025 | Journal Article | LibreCat-ID: 67316
Peitz, Sebastian, and Sedjro Salomon Hotegni. “Multi-Objective Deep Learning: Taxonomy and Survey of the State of the Art.” Machine Learning with Applications, no. 100700 (2025). https://doi.org/10.1016/j.mlwa.2025.100700.
LibreCat
| DOI
2024 | Conference Paper | LibreCat-ID: 46649 |
Hotegni, Sedjro Salomon, Manuel Bastian Berkemeier, and Sebastian Peitz. “Multi-Objective Optimization for Sparse Deep Multi-Task Learning.” In 2024 International Joint Conference on Neural Networks (IJCNN), 9. Yokohama, Japan: IEEE, 2024. https://doi.org/10.1109/IJCNN60899.2024.10650994.
LibreCat
| DOI
| Download (ext.)
2023 | Conference Paper | LibreCat-ID: 45695 |
Hotegni, Sedjro Salomon, Sepideh Mahabadi, and Ali Vakilian. “Approximation Algorithms for Fair Range Clustering.” In Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023., n.d.
LibreCat
| Download (ext.)