TRANI, SALVATORE
TRANI, SALVATORE
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Deep community detection in attributed temporal graphs: experimental evaluation of current approaches
2024 Passos Nelson, A. R. A.; Carlini, E.; Trani, S.
Distilled neural networks for efficient learning to rank: (Extended Abstract)
2024 Nardini, F. M.; Rulli, C.; Trani, S.; Venturini, R.
Early exit strategies for approximate k-NN search in dense retrieval
2024 Busolin, F.; Lucchese, C.; Nardini, F. M.; Orlando, S.; Perego, R.; Trani, S.
LongDoc summarization using instruction-tuned large language models for food safety regulations
2024 Rocchietti, G.; Rulli, C.; Randl, K.; Muntean, C.; Nardini, F. M.; Perego, R.; Trani, S.; Karvounis, M.; Janostik, J.
Early exit strategies for learning-to-rank cascades
2023 Busolin, F; Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S
A federated cloud solution for transnational mobility data sharing
2022 Carlini, E; Chevalier, T; Dazzi, P; Lettich, F; Perego, R; Renso, C; Trani, S
Distilled neural networks for efficient learning to rank
2022 Nardini, Fm; Rulli, C; Trani, S; Venturini, R
Energy-efficient ranking on FPGAs through ensemble model compression (Abstract)
2022 Gil-Costa, V.; Loor, F.; Molina, R.; Nardini, F. M.; Perego, R.; Trani, S.
Ensemble model compression for fast and energy-efficient ranking on FPGAs
2022 GilCosta V.; Loor F.; Molina R.; Nardini F.M.; Perego R.; Trani S.
Efficient traversal of decision tree ensembles with FPGAs
2021 Molina, R; Loor, F; Gilcosta, V; Nardini, Fm; Perego, R; Trani, S
Learning early exit strategies for additive ranking ensembles
2021 Busolin F.; Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Trani S.
Query-level early exit for additive learning-to-rank ensembles
2020 Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S
RankEval: Evaluation and investigation of ranking models
2020 Lucchese, C.; Muntean, C.; Nardini, F. M.; Perego, R.; Trani, S.
SEL: a unified algorithm for salient entity linking
2018 Trani S.; Lucchese C.; Perego R.; Losada D.E.; Ceccarelli D.; Orlando S.
Selective gradient boosting for effective learning to rank
2018 Lucchese, C; Nardini, F M; Perego, R; Orlando, S; Trani, S
X-CLEaVER: Learning ranking ensembles by growing and pruning trees
2018 Lucchese C.; Nardini F. M.; Orlando S.; Perego R.; Silvestri F.; Trani S.
RankEval: an evaluation and analysis framework for learning-to-rank solutions
2017 Lucchese C.; Muntean C.I.; Nardini F.M.; Perego R.; Trani S.
The impact of negative samples on learning to rank
2017 Lucchese C.; Nardini F.M.; Perego R.; Trani S.
X-DART: blending dropout and pruning for efficient learning to rank
2017 Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S
Improve ranking efficiency by optimizing tree ensembles
2016 Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Silvestri F.; Trani S.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| Deep community detection in attributed temporal graphs: experimental evaluation of current approaches | 1-gen-2024 | Passos Nelson, A. R. A.; Carlini, E.; Trani, S. | |
| Distilled neural networks for efficient learning to rank: (Extended Abstract) | 1-gen-2024 | Nardini, F. M.; Rulli, C.; Trani, S.; Venturini, R. | |
| Early exit strategies for approximate k-NN search in dense retrieval | 1-gen-2024 | Busolin, F.; Lucchese, C.; Nardini, F. M.; Orlando, S.; Perego, R.; Trani, S. | |
| LongDoc summarization using instruction-tuned large language models for food safety regulations | 1-gen-2024 | Rocchietti, G.; Rulli, C.; Randl, K.; Muntean, C.; Nardini, F. M.; Perego, R.; Trani, S.; Karvounis, M.; Janostik, J. | |
| Early exit strategies for learning-to-rank cascades | 1-gen-2023 | Busolin, F; Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S | |
| A federated cloud solution for transnational mobility data sharing | 1-gen-2022 | Carlini, E; Chevalier, T; Dazzi, P; Lettich, F; Perego, R; Renso, C; Trani, S | |
| Distilled neural networks for efficient learning to rank | 1-gen-2022 | Nardini, Fm; Rulli, C; Trani, S; Venturini, R | |
| Energy-efficient ranking on FPGAs through ensemble model compression (Abstract) | 1-gen-2022 | Gil-Costa, V.; Loor, F.; Molina, R.; Nardini, F. M.; Perego, R.; Trani, S. | |
| Ensemble model compression for fast and energy-efficient ranking on FPGAs | 1-gen-2022 | GilCosta V.; Loor F.; Molina R.; Nardini F.M.; Perego R.; Trani S. | |
| Efficient traversal of decision tree ensembles with FPGAs | 1-gen-2021 | Molina, R; Loor, F; Gilcosta, V; Nardini, Fm; Perego, R; Trani, S | |
| Learning early exit strategies for additive ranking ensembles | 1-gen-2021 | Busolin F.; Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Trani S. | |
| Query-level early exit for additive learning-to-rank ensembles | 1-gen-2020 | Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S | |
| RankEval: Evaluation and investigation of ranking models | 1-gen-2020 | Lucchese, C.; Muntean, C.; Nardini, F. M.; Perego, R.; Trani, S. | |
| SEL: a unified algorithm for salient entity linking | 1-gen-2018 | Trani S.; Lucchese C.; Perego R.; Losada D.E.; Ceccarelli D.; Orlando S. | |
| Selective gradient boosting for effective learning to rank | 1-gen-2018 | Lucchese, C; Nardini, F M; Perego, R; Orlando, S; Trani, S | |
| X-CLEaVER: Learning ranking ensembles by growing and pruning trees | 1-gen-2018 | Lucchese C.; Nardini F. M.; Orlando S.; Perego R.; Silvestri F.; Trani S. | |
| RankEval: an evaluation and analysis framework for learning-to-rank solutions | 1-gen-2017 | Lucchese C.; Muntean C.I.; Nardini F.M.; Perego R.; Trani S. | |
| The impact of negative samples on learning to rank | 1-gen-2017 | Lucchese C.; Nardini F.M.; Perego R.; Trani S. | |
| X-DART: blending dropout and pruning for efficient learning to rank | 1-gen-2017 | Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S | |
| Improve ranking efficiency by optimizing tree ensembles | 1-gen-2016 | Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Silvestri F.; Trani S. |