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SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks


Jul 16, 2022
Davide Buffelli, Pietro Liò, Fabio Vandin

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Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach


Jan 10, 2022
Davide Buffelli, Fabio Vandin

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* arXiv admin note: substantial text overlap with arXiv:2012.06755 

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odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks


Aug 19, 2021
Ilie Sarpe, Fabio Vandin

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* 14 pages, 8 figures, accepted at CIKM 2021 

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PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts


Jan 18, 2021
Ilie Sarpe, Fabio Vandin

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* 19 pages, 5 figures, to appear in SDM 2021 

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A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings


Dec 12, 2020
Davide Buffelli, Fabio Vandin

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* Accepted at the NeurIPS Workshop on Meta-Learning (MetaLearn) 2020 

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MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining


Jun 16, 2020
Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato

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Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation


Jun 06, 2020
Davide Buffelli, Fabio Vandin

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Are Graph Convolutional Networks Fully Exploiting Graph Structure?


Jun 06, 2020
Davide Buffelli, Fabio Vandin

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Scalable Distributed Approximation of Internal Measures for Clustering Evaluation


Mar 03, 2020
Federico Altieri, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin

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* 16 pages, 4 tables, 1 figure 

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Finding the True Frequent Itemsets


Jan 22, 2014
Matteo Riondato, Fabio Vandin

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* 13 pages, Extended version of work appeared in SIAM International Conference on Data Mining, 2014 

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