GizaML: A Collaborative Meta-learning Based Framework Using LLM For Automated Time-Series Forecasting

Esraa Sayed, Mohamed Maher, Omar Sedeek, Ahmed Eldamaty, Amr Kamel, Radwa El Shawi. GizaML: A Collaborative Meta-learning Based Framework Using LLM For Automated Time-Series Forecasting. In Letizia Tanca, Qiong Luo 0001, Giuseppe Polese, Loredana Caruccio, Xavier Oriol, Donatella Firmani, editors, Proceedings 27th International Conference on Extending Database Technology, EDBT 2024, Paestum, Italy, March 25 - March 28. pages 830-833, OpenProceedings.org, 2024. [doi]

@inproceedings{SayedMSEKS24,
  title = {GizaML: A Collaborative Meta-learning Based Framework Using LLM For Automated Time-Series Forecasting},
  author = {Esraa Sayed and Mohamed Maher and Omar Sedeek and Ahmed Eldamaty and Amr Kamel and Radwa El Shawi},
  year = {2024},
  doi = {10.48786/edbt.2024.81},
  url = {https://doi.org/10.48786/edbt.2024.81},
  researchr = {https://researchr.org/publication/SayedMSEKS24},
  cites = {0},
  citedby = {0},
  pages = {830-833},
  booktitle = {Proceedings 27th International Conference on Extending Database Technology, EDBT 2024, Paestum, Italy, March 25 - March 28},
  editor = {Letizia Tanca and Qiong Luo 0001 and Giuseppe Polese and Loredana Caruccio and Xavier Oriol and Donatella Firmani},
  publisher = {OpenProceedings.org},
  isbn = {978-3-89318-091-2},
}