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Gruppiert nach: Dokumententyp | Veröffentlichungsdatum
Springe zu: 2023 | 2020 | 2019 | 2018 | 2017
Anzahl der Publikationen: 6

2023

Kenneweg, Philip; Galli, Leonardo ORCID logoORCID: https://orcid.org/0000-0002-8045-7101; Kenneweg, Tristan und Hammer, Barbara (2023): Faster Convergence for Transformer Fine-tuning with Line Search Methods. International Joint Conference on Neural Networks (IJCNN), Queensland, 28. - 23. June 2023. In: 2023 International Joint Conference on Neural Networks (IJCNN), Piscataway Township, New Jersey: IEEE. S. 1-8

Galli, Leonardo ORCID logoORCID: https://orcid.org/0000-0002-8045-7101; Rauhut, Holger ORCID logoORCID: https://orcid.org/0000-0003-4750-5092 und Schmidt, Mark (2023): Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models. Advances in Neural Information Processing Systems, New Orleans, 10. - 16. December 2023.

2020

Galli, Leonardo ORCID logoORCID: https://orcid.org/0000-0002-8045-7101; Levato, Tommaso; Schoen, Fabio und Tigli, Luca (Juni 2020): Prescriptive analytics for inventory management in health care. In: Journal of the Operational Research Society, Bd. 72, Nr. 10: S. 2211-2224

2019

Galli, Leonardo ORCID logoORCID: https://orcid.org/0000-0002-8045-7101; Galligari, Alessandro und Sciandrone, Marco (November 2019): A unified convergence framework for nonmonotone inexact decomposition methods. In: Computational Optimization and Applications, Bd. 75, Nr. 1: S. 113-144

2018

Cocchi, Guido; Galli, Leonardo ORCID logoORCID: https://orcid.org/0000-0002-8045-7101; Galvan, Giulio; Sciandrone, Marco; Cantù, Matteo und Tomaselli, Giuseppe (2018): Machine learning methods for short‐term bid forecasting in the renewable energy market: A case study in Italy. In: Wind Energy, Bd. 21, Nr. 5: S. 285-371

2017

Galli, Leonardo ORCID logoORCID: https://orcid.org/0000-0002-8045-7101; Kanzow, Christian und Sciandrone, Marco (Oktober 2017): A nonmonotone trust-region method for generalized Nash equilibrium and related problems with strong convergence properties. In: Computational Optimization and Applications, Bd. 69: S. 629-652

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