| Fast approximation of betweenness centrality through sampling M Riondato, EM Kornaropoulos Proceedings of the 7th ACM international conference on Web search and data …, 2014 | 305 | 2014 |
| Learning-based query performance modeling and prediction M Akdere, U Çetintemel, M Riondato, E Upfal, SB Zdonik 2012 IEEE 28th International Conference on Data Engineering, 390-401, 2012 | 282 | 2012 |
| PARMA: A Parallel Randomized Algorithm for Approximate Association Rules Mining in MapReduce M Riondato, JA DeBrabant, R Fonseca, E Upfal CIKM 2012, 2012 | 169 | 2012 |
| Triest: Counting local and global triangles in fully dynamic streams with fixed memory size LD Stefani, A Epasto, M Riondato, E Upfal ACM Transactions on Knowledge Discovery from Data (TKDD) 11 (4), 1-50, 2017 | 159 | 2017 |
| Abra: Approximating betweenness centrality in static and dynamic graphs with rademacher averages M Riondato, E Upfal ACM Transactions on Knowledge Discovery from Data (TKDD) 12 (5), 1-38, 2018 | 143 | 2018 |
| Graph Summarization with Quality Guarantees M Riondato, D Garcıa-Soriano, F Bonchi ICDM, 2015 | 142 | 2015 |
| Space-round tradeoffs for MapReduce computations A Pietracaprina, G Pucci, M Riondato, F Silvestri, E Upfal Proceedings of the 26th ACM international conference on Supercomputing, 235-244, 2012 | 82 | 2012 |
| Efficient discovery of association rules and frequent itemsets through sampling with tight performance guarantees M Riondato, E Upfal ACM Transactions on Knowledge Discovery from Data (TKDD) 8 (4), 1-32, 2014 | 71 | 2014 |
| Mining frequent itemsets through progressive sampling with rademacher averages M Riondato, E Upfal Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 68 | 2015 |
| The Case for Predictive Database Systems: Opportunities and Challenges. M Akdere, U Cetintemel, M Riondato, E Upfal, SB Zdonik CIDR 2011, 167-174, 2011 | 54 | 2011 |
| Mining top-K frequent itemsets through progressive sampling A Pietracaprina, M Riondato, E Upfal, F Vandin Data Mining and Knowledge Discovery 21, 310-326, 2010 | 50 | 2010 |
| Centrality measures on big graphs: Exact, approximated, and distributed algorithms F Bonchi, G De Francisci Morales, M Riondato Proceedings of the 25th international conference companion on world wide web …, 2016 | 38 | 2016 |
| The VC-dimension of SQL queries and selectivity estimation through sampling M Riondato, M Akdere, U Çetintemel, SB Zdonik, E Upfal Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011 | 38 | 2011 |
| SPuManTE: Significant pattern mining with unconditional testing L Pellegrina, M Riondato, F Vandin Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 34 | 2019 |
| MaNIACS: Approximate Mining of Frequent Subgraph Patterns through Sampling G Preti, G De Francisci Morales, M Riondato ACM Transactions on Intelligent Systems and Technology 14 (3), 1-29, 2023 | 28 | 2023 |
| Repbublik: Reducing polarized bubble radius with link insertions S Haddadan, C Menghini, M Riondato, E Upfal Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 28 | 2021 |
| MCRapper: Monte-Carlo Rademacher averages for poset families and approximate pattern mining L Pellegrina, C Cousins, F Vandin, M Riondato ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (6), 1-29, 2022 | 25 | 2022 |
| The importance of being expert: Efficient max-finding in crowdsourcing A Anagnostopoulos, L Becchetti, A Fazzone, I Mele, M Riondato Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 25 | 2015 |
| Hypothesis testing and statistically-sound pattern mining L Pellegrina, M Riondato, F Vandin Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 23 | 2019 |
| Finding the True Frequent Itemsets M Riondato, F Vandin arXiv preprint arXiv:1301.1218, 2013 | 23 | 2013 |
Eli UpfalComputer Science Professor, Brown UniversityVerified email at brown.edu
