Ensemble Model Compression for Fast and Energy-Efficient Ranking on FPGAs

Author:

Gil-Costa VeronicaORCID,Loor FernandoORCID,Molina RominaORCID,Nardini Franco MariaORCID,Perego RaffaeleORCID,Trani SalvatoreORCID

Publisher

Springer International Publishing

Reference34 articles.

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4. Busolin, F., Lucchese, C., Nardini, F.M., Orlando, S., Perego, R., Trani, S.: Learning early exit strategies for additive ranking ensembles. In: Proceedings of SIGIR, pp. 2217–2221. ACM (2021)

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1. Post-hoc Selection of Pareto-Optimal Solutions in Search and Recommendation;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

2. Efficient and Effective Tree-based and Neural Learning to Rank;Foundations and Trends® in Information Retrieval;2023

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