Nicola Tonellotto

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Raffaele PeregoResearch Director, ISTI-CNREmail yang diverifikasi di isti.cnr.it
Craig MacdonaldSchool of Computing Science, University of GlasgowEmail yang diverifikasi di glasgow.ac.uk
Franco Maria NardiniSenior Researcher, ISTI-CNR, Pisa, ItalyEmail yang diverifikasi di isti.cnr.it
Iadh OunisProfessor at the University of Glasgow, School of Computing ScienceEmail yang diverifikasi di glasgow.ac.uk
Salvatore OrlandoProfessor of Computer Science, Università Ca' Foscari Venezia, ItalyEmail yang diverifikasi di unive.it
Fabrizio SilvestriSapienza, University of RomeEmail yang diverifikasi di uniroma1.it
Claudio LuccheseFull Professor, Ca' Foscari University of VeniceEmail yang diverifikasi di unive.it
Ophir FriederGeorgetown UniversityEmail yang diverifikasi di ir.cs.georgetown.edu
Rossano VenturiniAssociate Professor, Dept. of Computer Science, University of PisaEmail yang diverifikasi di unipi.it
Marco DaneluttoProfessor, Dept. of Computer Science, Univ. of PisaEmail yang diverifikasi di unipi.it
Sean MacAvaneyUniversity of GlasgowEmail yang diverifikasi di glasgow.ac.uk
Ida MeleIASI-CNR, Rome, ItalyEmail yang diverifikasi di iasi.cnr.it
Cristina Ioana MunteanISTI-CNR, PisaEmail yang diverifikasi di isti.cnr.it
Alberto GottaSenior Researcher @ National Research Council (CNR)Email yang diverifikasi di isti.cnr.it
Ranieri BaragliaISTI - CNREmail yang diverifikasi di isti.cnr.it
Marco AldinucciFull Professor in Computer Science, University of TorinoEmail yang diverifikasi di unito.it
Federico SicilianoPost-doc, Sapienza University of RomeEmail yang diverifikasi di diag.uniroma1.it
Antonio MalliaPineconeEmail yang diverifikasi di nyu.edu
Nazli GoharianGeorgetown UniversityEmail yang diverifikasi di ir.cs.georgetown.edu
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Ikuti

Nicola Tonellotto

Associate Professor, University of Pisa

Email yang diverifikasi di unipi.it - Beranda

Information Retrieval Cloud Computing Machine Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Declarative experimentation in information retrieval using PyTerrier C Macdonald, N Tonellotto Proceedings of the 2020 ACM SIGIR on International Conference on Theory of …, 2020	175	2020
Learning passage impacts for inverted indexes A Mallia, O Khattab, T Suel, N Tonellotto Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021	166	2021
The power of noise: Redefining retrieval for rag systems F Cuconasu, G Trappolini, F Siciliano, S Filice, C Campagnano, Y Maarek, ... Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024	134	2024
Efficient document re-ranking for transformers by precomputing term representations S MacAvaney, FM Nardini, R Perego, N Tonellotto, N Goharian, O Frieder Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020	133	2020
Fast ranking with additive ensembles of oblivious and non-oblivious regression trees D Dato, C Lucchese, FM Nardini, S Orlando, R Perego, N Tonellotto, ... ACM Transactions on Information Systems (TOIS) 35 (2), 1-31, 2016	125	2016
PyTerrier: Declarative experimentation in Python from BM25 to dense retrieval C Macdonald, N Tonellotto, S MacAvaney, I Ounis Proceedings of the 30th acm international conference on information …, 2021	109	2021
Expansion via prediction of importance with contextualization S MacAvaney, FM Nardini, R Perego, N Tonellotto, N Goharian, O Frieder Proceedings of the 43rd International ACM SIGIR conference on research and …, 2020	105	2020
Learning to predict response times for online query scheduling C Macdonald, N Tonellotto, I Ounis Proceedings of the 35th international ACM SIGIR conference on Research and …, 2012	104	2012
Quickscorer: A fast algorithm to rank documents with additive ensembles of regression trees C Lucchese, FM Nardini, S Orlando, R Perego, N Tonellotto, R Venturini Proceedings of the 38th International ACM SIGIR Conference on Research and …, 2015	100	2015
Behavioural skeletons in GCM: autonomic management of grid components M Aldinucci, S Campa, M Danelutto, M Vanneschi, P Kilpatrick, P Dazzi, ... 16th Euromicro Conference on Parallel, Distributed and Network-Based …, 2008	95	2008
Efficient and effective retrieval using selective pruning N Tonellotto, C Macdonald, I Ounis Proceedings of the sixth ACM international conference on Web search and data …, 2013	92	2013
A grid information service based on peer-to-peer D Puppin, S Moncelli, R Baraglia, N Tonellotto, F Silvestri Euro-Par 2005 Parallel Processing: 11th International Euro-Par Conference …, 2005	90	2005
Pseudo-relevance feedback for multiple representation dense retrieval X Wang, C Macdonald, N Tonellotto, I Ounis Proceedings of the 2021 ACM SIGIR International Conference on Theory of …, 2021	89	2021
Quality versus efficiency in document scoring with learning-to-rank models G Capannini, C Lucchese, FM Nardini, S Orlando, R Perego, N Tonellotto Information Processing & Management 52 (6), 1161-1177, 2016	74	2016
Efficient query processing for scalable web search N Tonellotto, C Macdonald, I Ounis Foundations and Trends® in Information Retrieval 12 (4-5), 319-500, 2018	72	2018
Faster BlockMax WAND with variable-sized blocks A Mallia, G Ottaviano, E Porciani, N Tonellotto, R Venturini Proceedings of the 40th international ACM SIGIR conference on research and …, 2017	68	2017
Neural network quantization in federated learning at the edge N Tonellotto, A Gotta, FM Nardini, D Gadler, F Silvestri Information Sciences 575, 417-436, 2021	62	2021
ColBERT-PRF: Semantic pseudo-relevance feedback for dense passage and document retrieval X Wang, C Macdonald, N Tonellotto, I Ounis ACM Transactions on the Web 17 (1), 1-39, 2023	55	2023
Upper-bound approximations for dynamic pruning C Macdonald, I Ounis, N Tonellotto ACM Transactions on Information Systems (TOIS) 29 (4), 1-28, 2011	49	2011
Exploiting CPU SIMD extensions to speed-up document scoring with tree ensembles C Lucchese, FM Nardini, S Orlando, R Perego, N Tonellotto, R Venturini Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016	48	2016

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