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ORCIDNicola Tonellotto
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- affiliation: University of Pisa, Department of Information Engineering, Italy
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2020 – today
- 2024
[j22]Saira Bano
, Nicola Tonellotto, Pietro Cassarà, Alberto Gotta:
FedCMD: A Federated Cross-modal Knowledge Distillation for Drivers' Emotion Recognition. ACM Trans. Intell. Syst. Technol. 15(3): 57:1-57:27 (2024)- [j21]Elias Bassani, Nicola Tonellotto, Gabriella Pasi:
Personalized Query Expansion with Contextual Word Embeddings. ACM Trans. Inf. Syst. 42(2): 61:1-61:35 (2024) - [c107]Pranav Kasela, Gabriella Pasi, Raffaele Perego, Nicola Tonellotto:
DESIRE-ME: Domain-Enhanced Supervised Information Retrieval Using Mixture-of-Experts. ECIR (2) 2024: 111-125 - [c106]Elias Bassani, Nicola Tonellotto:
indxr: A Python Library for Indexing File Lines. ECIR (5) 2024: 251-255 - [c105]Carlos Lassance, Hervé Déjean, Stéphane Clinchant, Nicola Tonellotto:
Two-Step SPLADE: Simple, Efficient and Effective Approximation of SPLADE. ECIR (2) 2024: 349-363 - [c104]Jacopo Cecchetti, Nicola Tonellotto, Raffaele Perego:
Learning to Rank for Non Independent and Identically Distributed Datasets. ICTIR 2024: 71-79 - [c103]Francesca Righetti, Nicola Tonellotto, Nicola Barsanti, Carlo Vallati:
Energy-efficient Orchestration Strategies for Function-as-a-Service Platforms. PerCom Workshops 2024: 290-295 - [c102]Aleksandr Vladimirovich Petrov, Craig Macdonald, Nicola Tonellotto:
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items. RecSys 2024: 912-917 - [c101]Florin Cuconasu, Giovanni Trappolini, Federico Siciliano, Simone Filice, Cesare Campagnano, Yoelle Maarek, Nicola Tonellotto, Fabrizio Silvestri:
The Power of Noise: Redefining Retrieval for RAG Systems. SIGIR 2024: 719-729 - [c100]Guglielmo Faggioli, Nicola Ferro, Raffaele Perego, Nicola Tonellotto:
Dimension Importance Estimation for Dense Information Retrieval. SIGIR 2024: 1318-1328 - [c99]Sean MacAvaney, Nicola Tonellotto:
A Reproducibility Study of PLAID. SIGIR 2024: 1411-1419 - [c98]Antonio Mallia, Torsten Suel, Nicola Tonellotto:
Faster Learned Sparse Retrieval with Block-Max Pruning. SIGIR 2024: 2411-2415 - [e9]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14608, Springer 2024, ISBN 978-3-031-56026-2 [contents] - [e8]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14609, Springer 2024, ISBN 978-3-031-56059-0 [contents] - [e7]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part III. Lecture Notes in Computer Science 14610, Springer 2024, ISBN 978-3-031-56062-0 [contents] - [e6]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 14611, Springer 2024, ISBN 978-3-031-56065-1 [contents] - [e5]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part V. Lecture Notes in Computer Science 14612, Springer 2024, ISBN 978-3-031-56068-2 [contents] - [e4]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part VI. Lecture Notes in Computer Science 14613, Springer 2024, ISBN 978-3-031-56071-2 [contents] - [i31]Florin Cuconasu, Giovanni Trappolini, Federico Siciliano, Simone Filice, Cesare Campagnano, Yoelle Maarek, Nicola Tonellotto, Fabrizio Silvestri:
The Power of Noise: Redefining Retrieval for RAG Systems. CoRR abs/2401.14887 (2024) - [i30]Pranav Kasela, Gabriella Pasi, Raffaele Perego, Nicola Tonellotto:
DESIRE-ME: Domain-Enhanced Supervised Information REtrieval using Mixture-of-Experts. CoRR abs/2403.13468 (2024) - [i29]Carlos Lassance, Hervé Déjean, Stéphane Clinchant, Nicola Tonellotto:
Two-Step SPLADE: Simple, Efficient and Effective Approximation of SPLADE. CoRR abs/2404.13357 (2024) - [i28]Sean MacAvaney, Nicola Tonellotto:
A Reproducibility Study of PLAID. CoRR abs/2404.14989 (2024) - [i27]Antonio Mallia, Torsten Suel, Nicola Tonellotto:
Faster Learned Sparse Retrieval with Block-Max Pruning. CoRR abs/2405.01117 (2024) - [i26]Andrea Bacciu, Enrico Palumbo, Andreas Damianou, Nicola Tonellotto, Fabrizio Silvestri:
Generating Query Recommendations via LLMs. CoRR abs/2405.19749 (2024) - [i25]Andrea Giuseppe Di Francesco, Christian Giannetti, Nicola Tonellotto, Fabrizio Silvestri:
Graph Neural Re-Ranking via Corpus Graph. CoRR abs/2406.11720 (2024) - [i24]Florin Cuconasu, Giovanni Trappolini, Nicola Tonellotto, Fabrizio Silvestri:
A Tale of Trust and Accuracy: Base vs. Instruct LLMs in RAG Systems. CoRR abs/2406.14972 (2024) - [i23]Filippo Betello, Antonio Purificato, Federico Siciliano, Giovanni Trappolini, Andrea Bacciu, Nicola Tonellotto, Fabrizio Silvestri:
A Reproducible Analysis of Sequential Recommender Systems. CoRR abs/2408.03873 (2024) - [i22]Aleksandr V. Petrov, Craig Macdonald, Nicola Tonellotto:
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items. CoRR abs/2408.09992 (2024) - 2023
- [j20]Saira Bano, Nicola Tonellotto, Pietro Cassarà, Alberto Gotta:
Artificial intelligence of things at the edge: Scalable and efficient distributed learning for massive scenarios. Comput. Commun. 205: 45-57 (2023) - [j19]Guglielmo Faggioli, Antonio Ferrara, Franco Maria Nardini, Nicola Tonellotto:
Report on the 13th Italian Information Retrieval Workshop (IIR 2023). SIGIR Forum 57(2): 8:1-8:12 (2023) - [j18]Xiao Wang, Craig MacDonald, Nicola Tonellotto, Iadh Ounis:
ColBERT-PRF: Semantic Pseudo-Relevance Feedback for Dense Passage and Document Retrieval. ACM Trans. Web 17(1): 3:1-3:39 (2023) - [c97]Andrea Bacciu, Florin Cuconasu, Federico Siciliano, Fabrizio Silvestri, Nicola Tonellotto, Giovanni Trappolini:
RRAML: Reinforced Retrieval Augmented Machine Learning. DP@AI*IA 2023: 29-37 - [c96]Antonio Acquavia, Craig Macdonald, Nicola Tonellotto:
Static Pruning for Multi-Representation Dense Retrieval. DocEng 2023: 7:1-7:10 - [c95]Guglielmo Faggioli, Nicola Ferro, Cristina Ioana Muntean, Raffaele Perego, Nicola Tonellotto:
A Spatial Approach to Predict Performance of Conversational Search Systems. IIR 2023: 41-46 - [c94]Andrea Bacciu, Federico Siciliano, Nicola Tonellotto, Fabrizio Silvestri:
Integrating Item Relevance in Training Loss for Sequential Recommender Systems. RecSys 2023: 1114-1119 - [c93]Marco Aldinucci, Elena Maria Baralis, Valeria Cardellini, Iacopo Colonnelli, Marco Danelutto, Sergio Decherchi, Giuseppe Di Modica, Luca Ferrucci, Marco Gribaudo, Francesco Iannone, Marco Lapegna, Doriana Medic, Giuseppa Muscianisi, Francesca Righetti, Eva Sciacca, Nicola Tonellotto, Mauro Tortonesi, Paolo Trunfio, Tullio Vardanega:
A Systematic Mapping Study of Italian Research on Workflows. SC Workshops 2023: 2065-2076 - [c92]Guglielmo Faggioli, Nicola Ferro, Cristina Ioana Muntean, Raffaele Perego, Nicola Tonellotto:
A Geometric Framework for Query Performance Prediction in Conversational Search. SIGIR 2023: 1355-1365 - [c91]Carlos Lassance, Simon Lupart, Hervé Déjean, Stéphane Clinchant, Nicola Tonellotto:
A Static Pruning Study on Sparse Neural Retrievers. SIGIR 2023: 1771-1775 - [c90]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Reproducibility, Replicability, and Insights into Dense Multi-Representation Retrieval Models: from ColBERT to Col. SIGIR 2023: 2552-2561 - [c89]Shahrokh Vahabi, Francesca Righetti, Carlo Vallati, Nicola Tonellotto:
Energy-Efficient Resource Management for Real-Time Applications in FaaS Edge Computing Platforms. UCC 2023: 39 - [c88]Saira Bano, Pietro Cassarà, Nicola Tonellotto, Alberto Gotta:
A Federated Channel Modeling System using Generative Neural Networks. VTC2023-Spring 2023: 1-5 - [e3]Franco Maria Nardini, Nicola Tonellotto, Guglielmo Faggioli, Antonio Ferrara:
Proceedings of the 13th Italian Information Retrieval Workshop (IIR 2023), Pisa, Italy, June 8-9, 2023. CEUR Workshop Proceedings 3448, CEUR-WS.org 2023 [contents] - [i21]Carlos Lassance, Simon Lupart, Hervé Déjean, Stéphane Clinchant, Nicola Tonellotto:
A Static Pruning Study on Sparse Neural Retrievers. CoRR abs/2304.12702 (2023) - [i20]Andrea Bacciu, Federico Siciliano, Nicola Tonellotto, Fabrizio Silvestri:
Integrating Item Relevance in Training Loss for Sequential Recommender Systems. CoRR abs/2305.10824 (2023) - [i19]Saira Bano, Pietro Cassarà, Nicola Tonellotto, Alberto Gotta:
A Federated Channel Modeling System using Generative Neural Networks. CoRR abs/2305.18856 (2023) - [i18]Andrea Bacciu, Florin Cuconasu, Federico Siciliano, Fabrizio Silvestri, Nicola Tonellotto, Giovanni Trappolini:
RRAML: Reinforced Retrieval Augmented Machine Learning. CoRR abs/2307.12798 (2023) - 2022
- [j17]Luca Cassano, Antonio Miele, Francesco Mione, Nicola Tonellotto, Carlo Vallati:
Design of Fault-Tolerant Distributed Cyber-Physical Systems for Smart Environments. IEEE Embed. Syst. Lett. 14(2): 79-82 (2022) - [c87]Sean MacAvaney, Nicola Tonellotto, Craig Macdonald:
Adaptive Re-Ranking with a Corpus Graph. CIKM 2022: 1491-1500 - [c86]Sean MacAvaney, Nicola Tonellotto, Craig Macdonald:
Adaptive Re-Ranking as an Information-Seeking Agent. CIKM Workshops 2022 - [c85]Guglielmo Faggioli, Marco Ferrante, Nicola Ferro, Raffaele Perego, Nicola Tonellotto:
A Dependency-Aware Utterances Permutation Strategy to Improve Conversational Evaluation. ECIR (1) 2022: 184-198 - [c84]Domenico Dato, Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
A Comprehensive Dataset for Modern Learning to Rank Solutions (Abstract). IIR 2022 - [c83]Nicola Tonellotto:
Pseudo-Relevance Feedback in the Era of Dense Retrieval. IIR 2022 - [c82]Saira Bano, Nicola Tonellotto, Alberto Gotta:
Drivers Stress Identification in Real-World Driving Tasks. PerCom Workshops 2022: 140-141 - [c81]Saira Bano, Nicola Tonellotto, Pietro Cassarà, Alberto Gotta:
KafkaFed: Two-Tier Federated Learning Communication Architecture for Internet of Vehicles. PerCom Workshops 2022: 515-520 - [c80]Guglielmo Faggioli, Marco Ferrante, Nicola Ferro, Raffaele Perego, Nicola Tonellotto:
Improving Conversational Evaluation via a Dependency-Aware Permutation Strategy. SEBD 2022: 375-382 - [c79]Artsiom Sauchuk, James Thorne, Alon Y. Halevy, Nicola Tonellotto, Fabrizio Silvestri:
On the Role of Relevance in Natural Language Processing Tasks. SIGIR 2022: 1785-1789 - [c78]Antonio Mallia, Joel Mackenzie, Torsten Suel, Nicola Tonellotto:
Faster Learned Sparse Retrieval with Guided Traversal. SIGIR 2022: 1901-1905 - [c77]Domenico Dato, Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
The Istella22 Dataset: Bridging Traditional and Neural Learning to Rank Evaluation. SIGIR 2022: 3099-3107 - [c76]Ida Mele, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
Context Propagation in Conversational Search Utterances Participation of the CNR Team in CAsT 2022. TREC 2022 - [c75]Saira Bano, Nicola Tonellotto, Pietro Cassarà, Alberto Gotta:
FedTCS: Federated Learning with Time-based Client Selection to Optimize Edge Resources. AI6G@WCCI 2022 - [c74]Simone Pampaloni, Nicola Tonellotto, Carlo Vallati:
Latency-Energy Tradeoffs in Federated Learning on Resource Constrained Edge Computing Systems. AI6G@WCCI 2022 - [i17]Antonio Mallia, Joel Mackenzie, Torsten Suel, Nicola Tonellotto:
Faster Learned Sparse Retrieval with Guided Traversal. CoRR abs/2204.11314 (2022) - [i16]Nicola Tonellotto:
Lecture Notes on Neural Information Retrieval. CoRR abs/2207.13443 (2022) - [i15]Sean MacAvaney, Nicola Tonellotto, Craig Macdonald:
Adaptive Re-Ranking with a Corpus Graph. CoRR abs/2208.08942 (2022) - [i14]Ophir Frieder, Ida Mele, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
Caching Historical Embeddings in Conversational Search. CoRR abs/2211.14155 (2022) - 2021
- [j16]Ida Mele, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Ophir Frieder:
Adaptive utterance rewriting for conversational search. Inf. Process. Manag. 58(6): 102682 (2021) - [j15]Nicola Tonellotto, Alberto Gotta, Franco Maria Nardini, Daniele Gadler, Fabrizio Silvestri:
Neural network quantization in federated learning at the edge. Inf. Sci. 575: 417-436 (2021) - [j14]Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Ophir Frieder:
Weighting Passages Enhances Accuracy. ACM Trans. Inf. Syst. 39(2): 11:1-11:11 (2021) - [c73]Craig Macdonald, Nicola Tonellotto:
On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval. CIKM 2021: 3318-3322 - [c72]Nicola Tonellotto, Craig Macdonald:
Query Embedding Pruning for Dense Retrieval. CIKM 2021: 3453-3457 - [c71]Craig Macdonald, Nicola Tonellotto, Sean MacAvaney, Iadh Ounis:
PyTerrier: Declarative Experimentation in Python from BM25 to Dense Retrieval. CIKM 2021: 4526-4533 - [c70]Craig Macdonald, Nicola Tonellotto, Sean MacAvaney:
IR From Bag-of-words to BERT and Beyond through Practical Experiments. CIKM 2021: 4861 - [c69]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval. ICTIR 2021: 297-306 - [c68]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
On Single and Multiple Representations in Dense Passage Retrieval. IIR 2021 - [c67]Antonio Mallia, Omar Khattab, Torsten Suel, Nicola Tonellotto:
Learning Passage Impacts for Inverted Indexes. SIGIR 2021: 1723-1727 - [c66]Guglielmo Faggioli, Marco Ferrante, Nicola Ferro, Raffaele Perego, Nicola Tonellotto:
Hierarchical Dependence-aware Evaluation Measures for Conversational Search. SIGIR 2021: 1935-1939 - [c65]Ida Mele, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
Finding Context through Utterance Dependencies in Search Conversations - Participation of the CNR Team in CAsT 2021. TREC 2021 - [i13]Antonio Mallia, Omar Khattab, Nicola Tonellotto, Torsten Suel:
Learning Passage Impacts for Inverted Indexes. CoRR abs/2104.12016 (2021) - [i12]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval. CoRR abs/2106.11251 (2021) - [i11]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
On Single and Multiple Representations in Dense Passage Retrieval. CoRR abs/2108.06279 (2021) - [i10]Nicola Tonellotto, Craig Macdonald:
Query Embedding Pruning for Dense Retrieval. CoRR abs/2108.10341 (2021) - [i9]Craig Macdonald, Nicola Tonellotto:
On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval. CoRR abs/2108.11480 (2021) - 2020
- [j13]Ida Mele, Nicola Tonellotto, Ophir Frieder, Raffaele Perego:
Topical result caching in web search engines. Inf. Process. Manag. 57(3): 102193 (2020) - [j12]Nicola Tonellotto, Craig Macdonald:
Using an Inverted Index Synopsis for Query Latency and Performance Prediction. ACM Trans. Inf. Syst. 38(3): 29:1-29:33 (2020) - [c64]Antonio Cisternino, Pietro Ducange, Nicola Tonellotto, Carlo Vallati:
Leveraging Cloud Infrastructures for Teaching Advanced Computer Engineering Classes - Experiences at the University of Pisa. HELMeTO 2020: 256-270 - [c63]Craig Macdonald, Nicola Tonellotto:
Declarative Experimentation in Information Retrieval using PyTerrier. ICTIR 2020: 161-168 - [c62]Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder:
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations. SIGIR 2020: 49-58 - [c61]Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder:
Training Curricula for Open Domain Answer Re-Ranking. SIGIR 2020: 529-538 - [c60]Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder:
Expansion via Prediction of Importance with Contextualization. SIGIR 2020: 1573-1576 - [c59]Ida Mele, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Ophir Frieder:
Topic Propagation in Conversational Search. SIGIR 2020: 2057-2060 - [c58]Ida Mele, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
Topical Enrichment of Conversational Search Utterances: Participation of the HPCLab-CNR Team in CAsT 2020. TREC 2020 - [i8]Ida Mele, Nicola Tonellotto, Ophir Frieder, Raffaele Perego:
Topical Result Caching in Web Search Engines. CoRR abs/2001.03010 (2020) - [i7]Ida Mele, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Ophir Frieder:
Topic Propagation in Conversational Search. CoRR abs/2004.14054 (2020) - [i6]Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder:
Expansion via Prediction of Importance with Contextualization. CoRR abs/2004.14245 (2020) - [i5]Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder:
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations. CoRR abs/2004.14255 (2020) - [i4]Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder:
Training Curricula for Open Domain Answer Re-Ranking. CoRR abs/2004.14269 (2020) - [i3]Craig Macdonald, Nicola Tonellotto:
Declarative Experimentation in Information Retrieval using PyTerrier. CoRR abs/2007.14271 (2020) - [i2]Michele Martelli, Pietro Cassarà, Antonio Virdis, Nicola Tonellotto:
The Internet of Ships. ERCIM News 2020(123) (2020)
2010 – 2019
- 2019
- [j11]Francesco Lettich, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini:
Parallel Traversal of Large Ensembles of Decision Trees. IEEE Trans. Parallel Distributed Syst. 30(9): 2075-2089 (2019) - [c57]Matteo Catena, Nicola Tonellotto:
Multiple Query Processing via Logic Function Factoring. SIGIR 2019: 937-940 - [c56]Matteo Catena, Ophir Frieder, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
Enhanced News Retrieval: Passages Lead the Way! SIGIR 2019: 1269-1272 - 2018
- [j10]Nicola Tonellotto, Craig Macdonald, Iadh Ounis:
Efficient Query Processing for Scalable Web Search. Found. Trends Inf. Retr. 12(4-5): 319-500 (2018) - [j9]Marco Meoni, Raffaele Perego, Nicola Tonellotto:
Dataset Popularity Prediction for Caching of CMS Big Data. J. Grid Comput. 16(2): 211-228 (2018) - [c55]Matteo Catena, Ophir Frieder, Nicola Tonellotto:
Efficient Energy Management in Distributed Web Search. CIKM 2018: 1555-1558 - [c54]Manlio Bacco, Matteo Catena, Tomaso de Cola, Alberto Gotta, Nicola Tonellotto:
Performance Analysis of WebRTC-Based Video Streaming Over Power Constrained Platforms. GLOBECOM 2018: 1-7 - [c53]Nicola Tonellotto, Craig Macdonald:
Efficient Query Processing Infrastructures: A half-day tutorial at SIGIR 2018. SIGIR 2018: 1403-1406 - [e2]Nicola Tonellotto, Luca Becchetti, Marko Tkalcic:
Proceedings of the 9th Italian Information Retrieval Workshop, Rome, Italy, May, 28-30, 2018. CEUR Workshop Proceedings 2140, CEUR-WS.org 2018 [contents] - 2017
- [j8]Matteo Catena, Nicola Tonellotto:
Energy-Efficient Query Processing in Web Search Engines. IEEE Trans. Knowl. Data Eng. 29(7): 1412-1425 (2017) - [c52]Craig Macdonald, Nicola Tonellotto:
Upper Bound Approximation for BlockMaxWand. ICTIR 2017: 273-276 - [c51]Francesco Lettich, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini:
Multicore/Manycore Parallel Traversal of Large Forests of Regression Trees. HPCS 2017: 915 - [c50]Matteo Catena, Nicola Tonellotto:
Recent Advances in Energy Efficient Query Processing. IIR 2017: 125-128 - [c49]Marco Meoni, Raffaele Perego, Nicola Tonellotto:
Popularity-Based Caching of CMS Datasets. PARCO 2017: 221-231 - [c48]Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini:
QuickScorer: Efficient Traversal of Large Ensembles of Decision Trees. ECML/PKDD (3) 2017: 383-387 - [c47]Craig MacDonald, Nicola Tonellotto, Iadh Ounis:
Efficient & Effective Selective Query Rewriting with Efficiency Predictions. SIGIR 2017: 495-504 - [c46]Antonio Mallia, Giuseppe Ottaviano, Elia Porciani, Nicola Tonellotto, Rossano Venturini:
Faster BlockMax WAND with Variable-sized Blocks. SIGIR 2017: 625-634 - 2016
- [j7]Gabriele Capannini, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto:
Quality versus efficiency in document scoring with learning-to-rank models. Inf. Process. Manag. 52(6): 1161-1177 (2016) - [j6]Domenico Dato, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini:
Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees. ACM Trans. Inf. Syst. 35(2): 15:1-15:31 (2016) - [c45]Francesco Lettich, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini:
GPU-based Parallelization of QuickScorer to Speed-up Document Ranking with Tree Ensembles. IIR 2016 - [c44]