Matteo Riondato

Head shot of Matteo Riondato by Andrea Podestà

Contact info

Publications

My publications and citations on: DBLP, Google Scholar, AMiner, ResearchGate, ORCID, ResearcherID, Scopus.

Here are BibTeX entries for my papers.

Many of the linked PDFs are extended versions of the original publications.

Journal Articles

  1. M. Riondato and E. Upfal ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages, ACM Tansactions on Knowledge Discovery from Data, to appear
  2. L. De Stefani, A. Epasto, M. Riondato, and E. Upfal. TRIÈST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size, ACM Tansactions on Knowledge Discovery from Data, 11(2):43, 2017
  3. M. Riondato, D. García-Soriano, and F. Bonchi. Graph Summarization with Quality Guarantees, Data Mining and Knowledge Discovery, 31(2):314—349
  4. M. Riondato and E. M. Kornaropoulos. Fast Approximation of Betweenness Centrality through Sampling, Data Mining and Knowledge Discovery, 30(2):438—475, 2016
  5. M. Riondato and E. Upfal. Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees, ACM Transactions on Knowledge Discovery from Data, 8(4):20, 2014
  6. A. Pietracaprina, M. Riondato, E. Upfal, and F. Vandin. Mining Top-k Frequent Itemsets through Progressive Sampling, Data Mining and Knowledge Discovery, 21(2):310—326, 2010

Conference Papers

  1. M. Riondato and E. Upfal ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages, ACM KDD'16, 2016
  2. L. De Stefani, A. Epasto, M. Riondato, and E. Upfal. TRIÈST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size, ACM KDD'16, 2016
  3. A. Mahmoody, M. Riondato, and E. Upfal. Wiggins: Detecting Valuable Information in Dynamic Networks with Limited Resources, ACM WSDM'16, 2016
  4. M. Riondato and E. Upfal. Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages, ACM KDD'15, 2015, Presentation Video
  5. A. Anagnastopoulos, L. Becchetti, A. Fazzone, I. Mele, and M. Riondato. The Importance of Being Experts: Efficient Max-Finding in Crowdsourcing, ACM SIGMOD'15, 2015
  6. M. Riondato, D. García-Soriano, and F. Bonchi. Graph Summarization with Quality Guarantees, IEEE ICDM'14, 2014
  7. M. Riondato. Sampling-based Data Mining Algorithms: Modern Techniques and Case Studies, ECML PKDD'14, 2014
  8. M. Riondato and F. Vandin. Finding the True Frequent Itemsets, SIAM SDM'14, 2014
  9. M. Riondato and E. M. Kornaropoulos. Fast Approximation of Betweenness Centrality through Sampling, ACM WSDM'14, 2014
  10. M. Riondato, J. A. DeBrabant, R. Fonseca, and E. Upfal. PARMA: A Parallel Randomized Algorithm for Association Rules Mining in MapReduce, ACM CIKM'12, 2012
  11. M. Riondato and E. Upfal. Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees, ECML PKDD'12, 2012
  12. A. Pietracaprina, G. Pucci, M. Riondato, F. Silvestri, and E. Upfal. Space-round Tradeoffs for MapReduce Computations, ACM ICS'12, 2012
  13. M. Akdere, U. Çetintemel, M. Riondato, E. Upfal, and S. B. Zdonik. Learning-based Query Performance Modeling and Prediction, IEEE ICDE'12, 2012
  14. M. Riondato, M. Akdere, U. Çetintemel, S. B. Zdonik, and E. Upfal. The VC-dimension of SQL Queries and Selectivity Estimation through Sampling, ECML PKDD'11, 2011
  15. M. Akdere, U. Çetintemel, M. Riondato, E. Upfal, and S. B. Zdonik. The Case for Predictive Database Systems: Opportunities and Challenges, CIDR'11, 2011

Tutorials

  1. F. Bonchi, G. De Francisci Morales, and M. Riondato. Centrality Measures on Big Graphs: Exact, Approximated, and Distributed Algorithms, WWW'16. Slides.
  2. M. Riondato and E. Upfal. VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms, ACM KDD'15, ECML PKDD'15, ACM CIKM'15. Slides, Video at KDD'15 (Part 1), Video at KDD'15 (Part 2)

PhD Dissertation

  1. M. Riondato. Sampling-based Randomized Algorithms for Big Data Analytics, Brown University Department of Computer Science, 2014

Other technical writings

  1. M. Riondato, Jails, in FreeBSD Handbook.

Coauthors

Mert Akdere, Aris Anagnostopoulos, Luca Becchetti, Francesco Bonchi, Uğur Çetintemel, Justin A. DeBrabant, Gianmarco De Francisci Morales, Lorenzo De Stefani, Rodrigo Fonseca, Alessandro Epasto, David García Soriano, Evgenios M. Kornaropoulos, Ahmad Mahmoody, Ida Mele, Andrea Pietracaprina, Geppino Pucci, Francesco Silvestri, Eli Upfal, Fabio Vandin, Stan B. Zdonik