| The PGM-index: a fully dynamic compressed learned index with provable worst-case bounds P Ferragina, G Vinciguerra PVLDB 13 (8), 1162-1175, 2020 | 222 | 2020 |
| Why Are Learned Indexes So Effective? P Ferragina, F Lillo, G Vinciguerra Proceedings of the 37th International Conference on Machine Learning (ICML), 2020 | 38 | 2020 |
| Learned Data Structures P Ferragina, G Vinciguerra Recent Trends in Learning From Data, 5-41, 2020 | 36 | 2020 |
| On the performance of learned data structures P Ferragina, F Lillo, G Vinciguerra Theoretical Computer Science 871, 107-120, 2021 | 30 | 2021 |
| A learned approach to design compressed rank/select data structures A Boffa, P Ferragina, G Vinciguerra ACM Transactions on Algorithms (TALG) 18 (3), 1-28, 2022 | 22 | 2022 |
| A “Learned” Approach to Quicken and Compress Rank/Select Dictionaries A Boffa, P Ferragina, G Vinciguerra Proceedings of the SIAM Symposium on Algorithm Engineering and Experiments …, 2021 | 22 | 2021 |
| On Nonlinear Learned String Indexing P Ferragina, M Frasca, GC Marinò, G Vinciguerra IEEE Access, 2023 | 6 | 2023 |
| Compressing and Querying Integer Dictionaries Under Linearities and Repetitions P Ferragina, G Manzini, G Vinciguerra IEEE Access 10, 118831-118848, 2022 | 5 | 2022 |
| Compressed string dictionaries via data-aware subtrie compaction A Boffa, P Ferragina, F Tosoni, G Vinciguerra International Symposium on String Processing and Information Retrieval, 233-249, 2022 | 5 | 2022 |
| Repetition-and Linearity-Aware Rank/Select Dictionaries P Ferragina, G Manzini, G Vinciguerra 32nd International Symposium on Algorithms and Computation (ISAAC 2021), 2021 | 5 | 2021 |
| Learned Monotone Minimal Perfect Hashing P Ferragina, HP Lehmann, P Sanders, G Vinciguerra European Symposium on Algorithms (ESA 2023), 2023 | 1 | 2023 |
| Engineering a Textbook Approach to Index Massive String Dictionaries P Ferragina, M Rotundo, G Vinciguerra International Symposium on String Processing and Information Retrieval …, 2023 | 1 | 2023 |
| Compression and search process on a data set based on multiple strategies P Ferragina, G Manzini, G Vinciguerra US Patent App. 17/938,626, 2024 | | 2024 |
| CoCo-trie: Data-aware compression and indexing of strings A Boffa, P Ferragina, F Tosoni, G Vinciguerra Information Systems 120, 102316, 2024 | | 2024 |
| Grafite: Taming Adversarial Queries with Optimal Range Filters M Costa, P Ferragina, G Vinciguerra Proceedings of the ACM on Management of Data 2 (3), 23, 2024 | | 2024 |
| Learning-based compressed data structures G Vinciguerra Università di Pisa, 2022 | | 2022 |
Paolo FerraginaProfessor of Algorithms, Dept. Computer Science, University of PisaVerified email at unipi.it
