Matteo Riondato

71 papers A* 17A 13Journal 31Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	DSP: A Statistically-Principled Structural Polarization Measure. WSDM Giulia Preti, Matteo Riondato, Aristides Gionis, Gianmarco De Francisci Morales
2026	A*	`conf`	HomeRun: Performing Curveball Trades quasi in Streaming for Fast Null Modeling of Graphs, Hypergraphs, and Binary Matrices. WWW Michelle Contreras-Catalan, Matteo Riondato
2026	—	`conf`	VaLUH: Fast Algorithms for the Configuration Model of Vertex-Labeled Undirected Hypergraphs. KDD (1) Maryam Abuissa, Matteo Riondato
2025	J	`jnl`	Alice and the Caterpillar: A more descriptive null model for assessing data mining results. CoRR Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato
2025	J	`jnl`	DSP: A Statistically-Principled Structural Polarization Measure. CoRR Giulia Preti, Matteo Riondato, Aristides Gionis, Gianmarco De Francisci Morales
2025	—	`conf`	DiNgHy: Null Models for Non-degenerate Directed Hypergraphs. ECML/PKDD (3) Maryam Abuissa, Matteo Riondato, Eli Upfal
2025	A	`conf`	Polaris: Sampling from the Multigraph Configuration Model with Prescribed Color Assortativity. WSDM Giulia Preti, Matteo Riondato, Aristides Gionis, Gianmarco De Francisci Morales
2025	A	`ed.`	Proceedings of the 2025 SIAM International Conference on Data Mining, SDM 2025, Alexandria, VA, USA, May 1-3, 2025 SDM Vagelis Papalexakis, Matteo Riondato, Elena Zheleva, Tim Weninger, Wei Ding
2024	J	`jnl`	Alice and the Caterpillar: A more descriptive null model for assessing data mining results. Knowl. Inf. Syst. Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato
2024	—	`conf`	ClaveNet: Generating Afro-Cuban Drum Patterns through Data Augmentation. Audio Mostly Conference Daniel Flores García, Hugo Flores García, Matteo Riondato
2024	J	`jnl`	Polaris: Sampling from the Multigraph Configuration Model with Prescribed Color Assortativity. CoRR Giulia Preti, Matteo Riondato, Aristides Gionis, Gianmarco De Francisci Morales
2024	A	`ed.`	Proceedings of the 2024 SIAM International Conference on Data Mining, SDM 2024, Houston, TX, USA, April 18-20, 2024 SDM Shashi Shekhar, Vagelis Papalexakis, Jing Gao, Zhe Jiang, Matteo Riondato
2024	J	`jnl`	Statistical and Probabilistic Methods in Algorithmic Data Analysis (Dagstuhl Seminar 24391). Dagstuhl Reports Aristides Gionis, Matteo Riondato, Eli Upfal
2023	J	`jnl`	An impossibility result for Markov Chain Monte Carlo sampling from micro-canonical bipartite graph ensembles. CoRR Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato
2023	J	`jnl`	Bavarian: Betweenness Centrality Approximation with Variance-aware Rademacher Averages. ACM Trans. Knowl. Discov. Data Cyrus Cousins, Chloe Wohlgemuth, Matteo Riondato
2023	J	`jnl`	MaNIACS: Approximate Mining of Frequent Subgraph Patterns through Sampling. ACM Trans. Intell. Syst. Technol. Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato
2023	J	`jnl`	ROhAN: Row-order agnostic null models for statistically-sound knowledge discovery. Data Min. Knowl. Discov. Maryam Abuissa, Alexander W. Lee, Matteo Riondato
2023	—	`conf`	Statistically-Sound Knowledge Discovery from Data: Challenges and Directions. CogMI Matteo Riondato
2023	A	`conf`	Statistically-sound Knowledge Discovery from Data. SDM Matteo Riondato
2022	A*	`conf`	A Scalable Parallel Algorithm for Balanced Sampling (Student Abstract). AAAI Alexander W. Lee, Stefan Walzer-Goldfeld, Shukry Zablah, Matteo Riondato
2022	A*	`conf`	Alice and the Caterpillar: A More Descriptive Null Model for Assessing Data Mining Results. ICDM Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato
2022	J	`jnl`	MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. ACM Trans. Knowl. Discov. Data Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
2022	A	`ed.`	Proceedings of the 2022 SIAM International Conference on Data Mining, SDM 2022, Alexandria, VA, USA, April 28-30, 2022 SDM Arindam Banerjee, Zhi-Hua Zhou, Evangelos E. Papalexakis, Matteo Riondato
2022	J	`jnl`	Reducing polarization and increasing diverse navigability in graphs by inserting edges and swapping edge weights. Data Min. Knowl. Discov. Shahrzad Haddadan, Cristina Menghini, Matteo Riondato, Eli Upfal
2022	J	`jnl`	SPEck: mining statistically-significant sequential patterns efficiently with exact sampling. Data Min. Knowl. Discov. Steedman Jenkins, Stefan Walzer-Goldfeld, Matteo Riondato
2021	A*	`conf`	Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages. KDD Cyrus Cousins, Chloe Wohlgemuth, Matteo Riondato
2021	A*	`conf`	MaNIACS: Approximate Mining of Frequent Subgraph Patterns through Sampling. KDD Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato
2021	A	`conf`	RePBubLik: Reducing Polarized Bubble Radius with Link Insertions. WSDM Shahrzad Haddadan, Cristina Menghini, Matteo Riondato, Eli Upfal
2021	J	`jnl`	RePBubLik: Reducing the Polarized Bubble Radius with Link Insertions. CoRR Shahrzad Haddadan, Cristina Menghini, Matteo Riondato, Eli Upfal
2021	J	`jnl`	TipTap: Approximate Mining of Frequent ACM Trans. Knowl. Discov. Data Muhammad Anis Uddin Nasir, Çigdem Aslay, Gianmarco De Francisci Morales, Matteo Riondato
2020	A*	`conf`	MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. KDD Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
2020	J	`jnl`	MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. CoRR Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
2020	J	`jnl`	MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. ACM Trans. Knowl. Discov. Data Matteo Riondato, Fabio Vandin
2020	J	`jnl`	ProSecCo: progressive sequence mining with convergence guarantees. Knowl. Inf. Syst. Sacha Servan-Schreiber, Matteo Riondato, Emanuel Zgraggen
2020	A*	`conf`	Sharp uniform convergence bounds through empirical centralization. NeurIPS Cyrus Cousins, Matteo Riondato
2019	J	`jnl`	CaDET: interpretable parametric conditional density estimation with decision trees and forests. Mach. Learn. Cyrus Cousins, Matteo Riondato
2019	A*	`conf`	Hypothesis Testing and Statistically-sound Pattern Mining. KDD Leonardo Pellegrina, Matteo Riondato, Fabio Vandin
2019	A*	`conf`	SPuManTE: Significant Pattern Mining with Unconditional Testing. KDD Leonardo Pellegrina, Matteo Riondato, Fabio Vandin
2018	J	`jnl`	ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. ACM Trans. Knowl. Discov. Data Matteo Riondato, Eli Upfal
2018	A*	`conf`	MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. KDD Matteo Riondato, Fabio Vandin
2018	A*	`conf`	ProSecCo: Progressive Sequence Mining with Convergence Guarantees. ICDM Sacha Servan-Schreiber, Matteo Riondato, Emanuel Zgraggen
2017	J	`jnl`	Graph summarization with quality guarantees. Data Min. Knowl. Discov. Matteo Riondato, David García-Soriano, Francesco Bonchi
2017	J	`jnl`	TRIÈST: Counting Local and Global Triangles in Fully Dynamic Streams with Fixed Memory Size. ACM Trans. Knowl. Discov. Data Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal
2016	A*	`conf`	ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. KDD Matteo Riondato, Eli Upfal
2016	J	`jnl`	ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. CoRR Matteo Riondato, Eli Upfal
2016	—	`conf`	Centrality Measures on Big Graphs: Exact, Approximated, and Distributed Algorithms. WWW (Companion Volume) Francesco Bonchi, Gianmarco De Francisci Morales, Matteo Riondato
2016	J	`jnl`	Fast approximation of betweenness centrality through sampling. Data Min. Knowl. Discov. Matteo Riondato, Evgenios M. Kornaropoulos
2016	A*	`conf`	TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size. KDD Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal
2016	J	`jnl`	TRIÈST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size. CoRR Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal
2016	A	`conf`	Wiggins: Detecting Valuable Information in Dynamic Networks Using Limited Resources. WSDM Ahmad Mahmoody, Matteo Riondato, Eli Upfal
2015	A*	`conf`	Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages. KDD Matteo Riondato, Eli Upfal
2015	—	`conf`	The Importance of Being Expert: Efficient Max-Finding in Crowdsourcing. SIGMOD Conference Aris Anagnostopoulos, Luca Becchetti, Adriano Fazzone, Ida Mele, Matteo Riondato
2015	A*	`conf`	VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms. KDD Matteo Riondato, Eli Upfal
2014	J	`jnl`	Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees. ACM Trans. Knowl. Discov. Data Matteo Riondato, Eli Upfal
2014	A	`conf`	Fast approximation of betweenness centrality through sampling. WSDM Matteo Riondato, Evgenios M. Kornaropoulos
2014	A	`conf`	Finding the True Frequent Itemsets. SDM Matteo Riondato, Fabio Vandin
2014	A*	`conf`	Graph Summarization with Quality Guarantees. ICDM Matteo Riondato, David García-Soriano, Francesco Bonchi
2014	—	`conf`	Sampling-Based Data Mining Algorithms: Modern Techniques and Case Studies. ECML/PKDD (3) Matteo Riondato
2014	—	`—`	Sampling-based Randomized Algorithms for Big Data Analytics. Matteo Riondato
2013	J	`jnl`	Controlling False Positives in Frequent Itemsets Mining through the VC-Dimension CoRR Matteo Riondato, Fabio Vandin
2012	—	`conf`	Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees. ECML/PKDD (1) Matteo Riondato, Eli Upfal
2012	A*	`conf`	Learning-based Query Performance Modeling and Prediction. ICDE Mert Akdere, Ugur Çetintemel, Matteo Riondato, Eli Upfal, Stanley B. Zdonik
2012	A	`conf`	PARMA: a parallel randomized algorithm for approximate association rules mining in MapReduce. CIKM Matteo Riondato, Justin A. DeBrabant, Rodrigo Fonseca, Eli Upfal
2012	A	`conf`	Space-round tradeoffs for MapReduce computations. ICS Andrea Pietracaprina, Geppino Pucci, Matteo Riondato, Francesco Silvestri, Eli Upfal
2011	J	`jnl`	Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees CoRR Matteo Riondato, Eli Upfal
2011	J	`jnl`	Space-Round Tradeoffs for MapReduce Computations CoRR Andrea Pietracaprina, Geppino Pucci, Matteo Riondato, Francesco Silvestri, Eli Upfal
2011	A	`conf`	The Case for Predictive Database Systems: Opportunities and Challenges. CIDR Mert Akdere, Ugur Çetintemel, Matteo Riondato, Eli Upfal, Stanley B. Zdonik
2011	J	`jnl`	The VC-Dimension of Queries and Selectivity Estimation Through Sampling CoRR Matteo Riondato, Mert Akdere, Ugur Çetintemel, Stanley B. Zdonik, Eli Upfal
2011	—	`conf`	The VC-Dimension of SQL Queries and Selectivity Estimation through Sampling. ECML/PKDD (2) Matteo Riondato, Mert Akdere, Ugur Çetintemel, Stanley B. Zdonik, Eli Upfal
2010	J	`jnl`	Mining Top-K Frequent Itemsets Through Progressive Sampling CoRR Andrea Pietracaprina, Matteo Riondato, Eli Upfal, Fabio Vandin
2010	J	`jnl`	Mining top- Data Min. Knowl. Discov. Andrea Pietracaprina, Matteo Riondato, Eli Upfal, Fabio Vandin