LUCCHESE, CLAUDIO
LUCCHESE, CLAUDIO
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
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.
Efficient and effective query expansion for web search
2018 Lucchese C.; Nardini F. M.; Perego R.; Trani R.; Venturini R.
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.
Efficiency/Effectiveness trade-offs in learning to rank
2017 Lucchese, C; Nardini, Fm
Fast connected components computation in large graphs by vertex pruning
2017 Lulli, A; Carlini, E; Dazzi, P; Lucchese, C; Ricci, L
LEARning Next gEneration Rankers (LEARNER 2017)
2017 Ferro N.; Lucchese C.; Maistro M.; Perego R.
Multicore/Manycore parallel traversal of large forests of regression trees
2017 Lettich, F; Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Tonellotto, N; Venturini, R
On including the user dynamic in learning to rank
2017 Ferro, N; Lucchese, C; Maistro, M; Perego, R
Perception of social phenomena through the multidimensional analysis of online social networks
2017 Coletto M.; Esuli A.; Lucchese C.; Muntean C.I.; Nardini F.M.; Perego R.; Renso C.
QuickScorer: efficient traversal of large ensembles of decision trees
2017 Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Tonellotto N.; Venturini R.
RankEval: an evaluation and analysis framework for learning-to-rank solutions
2017 Lucchese C.; Muntean C.I.; Nardini F.M.; Perego R.; Trani S.
SELEcTor: Discovering Similar Entities on LinkEd DaTa by Ranking Their Features
2017 Ruback, L; Casanova, Ma; Renso, C; Lucchese, C
Sentiment spreading: an epidemic model for lexicon-based sentiment analysis on Twitter
2017 Pollacci L.; Sirbu A.; Giannotti F.; Pedreschi D.; Lucchese C.; Muntean C.I.
X-DART: blending dropout and pruning for efficient learning to rank
2017 Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S
Evaluating top-K approximate patterns via text clustering
2016 Lucchese, C; Orlando, S; Perego, R
Exploiting CPU SIMD extensions to speed-up document scoring with tree ensembles
2016 Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Tonellotto N.; Venturini R.
Fast feature selection for learning to rank
2016 Gigli A.; Lucchese C.; Nardini F.M.; Perego R.
Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees
2016 Dato D.; Lucchese C.; Nardini F. M.; Orlando S.; Perego R.; Tonellotto N.; Venturini R.
Titolo | Data di pubblicazione | Autore(i) | File |
---|---|---|---|
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. | |
Efficient and effective query expansion for web search | 1-gen-2018 | Lucchese C.; Nardini F. M.; Perego R.; Trani R.; Venturini R. | |
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. | |
Efficiency/Effectiveness trade-offs in learning to rank | 1-gen-2017 | Lucchese, C; Nardini, Fm | |
Fast connected components computation in large graphs by vertex pruning | 1-gen-2017 | Lulli, A; Carlini, E; Dazzi, P; Lucchese, C; Ricci, L | |
LEARning Next gEneration Rankers (LEARNER 2017) | 1-gen-2017 | Ferro N.; Lucchese C.; Maistro M.; Perego R. | |
Multicore/Manycore parallel traversal of large forests of regression trees | 1-gen-2017 | Lettich, F; Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Tonellotto, N; Venturini, R | |
On including the user dynamic in learning to rank | 1-gen-2017 | Ferro, N; Lucchese, C; Maistro, M; Perego, R | |
Perception of social phenomena through the multidimensional analysis of online social networks | 1-gen-2017 | Coletto M.; Esuli A.; Lucchese C.; Muntean C.I.; Nardini F.M.; Perego R.; Renso C. | |
QuickScorer: efficient traversal of large ensembles of decision trees | 1-gen-2017 | Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Tonellotto N.; Venturini R. | |
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. | |
SELEcTor: Discovering Similar Entities on LinkEd DaTa by Ranking Their Features | 1-gen-2017 | Ruback, L; Casanova, Ma; Renso, C; Lucchese, C | |
Sentiment spreading: an epidemic model for lexicon-based sentiment analysis on Twitter | 1-gen-2017 | Pollacci L.; Sirbu A.; Giannotti F.; Pedreschi D.; Lucchese C.; Muntean C.I. | |
X-DART: blending dropout and pruning for efficient learning to rank | 1-gen-2017 | Lucchese, C; Nardini, Fm; Orlando, S; Perego, R; Trani, S | |
Evaluating top-K approximate patterns via text clustering | 1-gen-2016 | Lucchese, C; Orlando, S; Perego, R | |
Exploiting CPU SIMD extensions to speed-up document scoring with tree ensembles | 1-gen-2016 | Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Tonellotto N.; Venturini R. | |
Fast feature selection for learning to rank | 1-gen-2016 | Gigli A.; Lucchese C.; Nardini F.M.; Perego R. | |
Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees | 1-gen-2016 | Dato D.; Lucchese C.; Nardini F. M.; Orlando S.; Perego R.; Tonellotto N.; Venturini R. |