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Ph.D. thesis

• Gradient Boosting Extensions

  Emami, Seyedsaman. "Gradient Boosting Extensions." (2024).

Peer-reviewed papers

• Learning Shared Economic Representations through the Application of Multi-Task Gradient Boosting

  Shahin, T., Emami, S. Learning Shared Economic Representations through the Application of Multi-Task Gradient Boosting. Comput Econ (2026). DOI: 10.1007/s10614-026-11358-z

• Robust-Multi-Task Gradient Boosting

  Emami, S., Martínez-Muñoz, G., Hernández-Lobato, D. Robust-Multi-Task Gradient Boosting. Expert Syst. Appl. 2025, 130696, DOI: 10.1016/j.eswa.2025.130696

• Condensed-gradient boosting

  Emami, S., Martínez-Muñoz, G. Condensed-gradient boosting. Int. J. Mach. Learn. & Cyber. 16, 687-701 (2025), DOI: DOI: 10.1007/s13042-024-02279-0

• Deep Learning for Multi-Output Regression using Gradient Boosting

  S. Emami and G. Martínez-Muñoz, “Deep Learning for Multi-Output Regression using Gradient Boosting”, in IEEE Access, vol. 12, pp. 17760-17772, 2024, DOI: 10.1109/ACCESS.2024.3359115

• A Gradient Boosting Approach for Training Convolutional and Deep Neural Networks

  S. Emami and G. Martínez-Muñoz, “A Gradient Boosting Approach for Training Convolutional and Deep Neural Networks”, in IEEE Open Journal of Signal Processing, vol. 4, pp. 313-321, 2023, DOI: 10.1109/OJSP.2023.3279011

• Sequential Training of Neural Networks with Gradient Boosting

  S. Emami and G. Martínez-Muñoz, "Sequential Training of Neural Networks with Gradient Boosting", in IEEE Access, vol. 11, pp. 42738-42750, 2023, DOI: 10.1109/ACCESS.2023.3271515

Conferences

• Multi-Task Gradient Boosting

  S. Emami, C. Ruiz Pastor, G. Martínez-Muñoz, “Multi-Task Gradient Boosting”, In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham, DOI: 10.1007/978-3-031-40725-3_9

• Multioutput Regression Neural Network Training via Gradient Boosting

  S. Emami, and G. Martínez-Muñoz, “Multioutput Regression Neural Network Training via Gradient Boosting”, In 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2022, Bruges, Belgium, October 5-7, 2022, (pp. 95-100), DOI: 10.14428/esann/2022.ES2022-95