Fabio Vandin

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 58

Top Topics

Top Venues

J. Comput. Biol.

Publications

Ilie Sarpe, Fabio Vandin, Aristides Gionis
Scalable Temporal Motif Densest Subnetwork Discovery. CoRR (2024)
Ilie Sarpe, Fabio Vandin, Aristides Gionis
Scalable Temporal Motif Densest Subnetwork Discovery. KDD (2024)
Leonardo Pellegrina, Fabio Vandin
Scalable Rule Lists Learning with Sampling. CoRR (2024)
Leonardo Pellegrina, Fabio Vandin
Efficient Discovery of Significant Patterns with Few-Shot Resampling. CoRR (2024)
Leonardo Pellegrina, Fabio Vandin
SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds. ACM Trans. Knowl. Discov. Data 18 (3) (2024)
Leonardo Pellegrina, Fabio Vandin
Scalable Rule Lists Learning with Sampling. KDD (2024)
Andrea Tonon, Fabio Vandin
caSPiTa: mining statistically significant paths in time series data from an unknown network. Knowl. Inf. Syst. 65 (6) (2023)
Dario Simionato, Fabio Vandin
Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages (Extended Abstract). IJCAI (2023)
Paolo Pellizzoni, Fabio Vandin
VC-dimension and Rademacher Averages of Subgraphs, with Applications to Graph Mining. ICDE (2023)
Davide Buffelli, Fabio Vandin
Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach. CoRR (2022)
Davide Buffelli, Fabio Vandin
Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach. IJCNN (2022)
Andrea Tonon, Fabio Vandin
gRosSo: mining statistically robust patterns from a sequence of datasets. Knowl. Inf. Syst. 64 (9) (2022)
Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. ACM Trans. Knowl. Discov. Data 16 (6) (2022)
Davide Buffelli, Pietro Lió, Fabio Vandin
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. NeurIPS (2022)
Davide Buffelli, Fabio Vandin
The Impact of Global Structural Information in Graph Neural Networks Applications. Data 7 (1) (2022)
Dario Simionato, Fabio Vandin
Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages. ECML/PKDD (5) (2022)
Fabio Vandin
Technical perspective: Evaluating sampled metrics is challenging. Commun. ACM 65 (7) (2022)
Davide Buffelli, Pietro Liò, Fabio Vandin
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. CoRR (2022)
Diego Santoro, Leonardo Pellegrina, Matteo Comin, Fabio Vandin
-mers by sampling reads, and applications. Bioinform. 38 (13) (2022)
Andrea Tonon, Fabio Vandin
CASPITA: Mining Statistically Significant Paths in Time Series Data from an Unknown Network. ICDM (2021)
Ilie Sarpe, Fabio Vandin
odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks. CoRR (2021)
Federico Altieri, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin
Scalable Distributed Approximation of Internal Measures for Clustering Evaluation. SDM (2021)
Ilie Sarpe, Fabio Vandin
PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts. SDM (2021)
Ilie Sarpe, Fabio Vandin
PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts. CoRR (2021)
Leonardo Pellegrina, Fabio Vandin
SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds. CoRR (2021)
Ilie Sarpe, Fabio Vandin
odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks. CIKM (2021)
Matteo Comin, Barbara Di Camillo, Cinzia Pizzi, Fabio Vandin
Comparison of microbiome samples: methods and computational challenges. Briefings Bioinform. 22 (1) (2021)
Leonardo Pellegrina, Fabio Vandin
Efficient mining of the most significant patterns with permutation testing. Data Min. Knowl. Discov. 34 (4) (2020)
Federico Altieri, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin
Scalable Distributed Approximation of Internal Measures for Clustering Evaluation. CoRR (2020)
Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. CoRR (2020)
Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. KDD (2020)
Matteo Riondato, Fabio Vandin
MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. ACM Trans. Knowl. Discov. Data 14 (5) (2020)
Diego Santoro, Andrea Tonon, Fabio Vandin
Mining Sequential Patterns with VC-Dimension and Rademacher Complexity. Algorithms 13 (5) (2020)
Davide Buffelli, Fabio Vandin
A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings. CoRR (2020)
Davide Buffelli, Fabio Vandin
Are Graph Convolutional Networks Fully Exploiting Graph Structure? CoRR (2020)
Leonardo Pellegrina, Cinzia Pizzi, Fabio Vandin
Fast Approximation of Frequent k-Mers and Applications to Metagenomics. J. Comput. Biol. 27 (4) (2020)
Andrea Tonon, Fabio Vandin
GRosSo: Mining Statistically Robust Patterns from a Sequence of Datasets. ICDM (2020)
Davide Buffelli, Fabio Vandin
Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation. CoRR (2020)
Leonardo Pellegrina, Matteo Riondato, Fabio Vandin
Hypothesis Testing and Statistically-sound Pattern Mining. KDD (2019)
Morteza Chalabi Hajkarim, Vasileios Tsiamis, Lukas Käll, Fabio Vandin, Veit Schwämmle
CoExpresso: assess the quantitative behavior of protein complexes in human cells. BMC Bioinform. 20 (1) (2019)
Leonardo Pellegrina, Cinzia Pizzi, Fabio Vandin
Fast Approximation of Frequent k-mers and Applications to Metagenomics. RECOMB (2019)
Leonardo Pellegrina, Matteo Riondato, Fabio Vandin
SPuManTE: Significant Pattern Mining with Unconditional Testing. KDD (2019)
Rebecca Sarto Basso, Dorit S. Hochbaum, Fabio Vandin
Efficient algorithms to discover alterations with complementary functional association in cancer. PLoS Comput. Biol. 15 (5) (2019)
Morteza Chalabi Hajkarim, Eli Upfal, Fabio Vandin
Differentially mutated subnetworks discovery. Algorithms Mol. Biol. 14 (1) (2019)
Andrea Tonon, Fabio Vandin
Permutation Strategies for Mining Significant Sequential Patterns. ICDM (2019)
Leonardo Pellegrina, Fabio Vandin
Efficient Mining of the Most Significant Patterns with Permutation Testing. KDD (2018)
Matteo Riondato, Fabio Vandin
MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. KDD (2018)
Morteza Chalabi Hajkarim, Eli Upfal, Fabio Vandin
Differentially Mutated Subnetworks Discovery. WABI (2018)
Rebecca Sarto Basso, Dorit S. Hochbaum, Fabio Vandin
Efficient Algorithms to Discover Alterations with Complementary Functional Association in Cancer. RECOMB (2018)
Diogo Almeida, Ida Skov, Artur Silva, Fabio Vandin, Qihua Tan, Richard Röttger, Jan Baumbach
Efficient detection of differentially methylated regions using DiMmeR. Bioinform. 33 (4) (2017)
Matteo Ceccarello, Carlo Fantozzi, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin
Clustering Uncertain Graphs. Proc. VLDB Endow. 11 (4) (2017)
Farhad Hormozdiari, Fereydoun Hormozdiari, Carl Kingsford, Paul Medvedev, Fabio Vandin
The Second Decade of the International Conference on Research in Computational Molecular Biology (RECOMB). RECOMB (2016)
Anna Bomersbach, Marco Chiarandini, Fabio Vandin
An Efficient Branch and Cut Algorithm to Find Frequently Mutated Subnetworks in Cancer. WABI (2016)
Lorenzo De Stefani, Alessandro Epasto, Eli Upfal, Fabio Vandin
Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic. AAAI (2016)
Diogo Almeida, Ida Skov, Jesper Lund, Afsaneh Mohammadnejad, Artur Silva, Fabio Vandin, Qihua Tan, Jan Baumbach, Richard Röttger
Jllumina - A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and MethylationEPIC data processing. J. Integr. Bioinform. 13 (4) (2016)
Matteo Ceccarello, Carlo Fantozzi, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin
Clustering Uncertain Graphs. CoRR (2016)
Tommy Hansen, Fabio Vandin
Finding Mutated Subnetworks Associated with Survival in Cancer. RECOMB (2016)
Fabio Vandin, Benjamin J. Raphael, Eli Upfal
On the Sample Complexity of Cancer Pathways Identification. J. Comput. Biol. 23 (1) (2016)
Fabio Vandin, Benjamin J. Raphael, Eli Upfal
On the Sample Complexity of Cancer Pathways Identification. RECOMB (2015)
Fabio Vandin, Alexandra Papoutsaki, Benjamin J. Raphael, Eli Upfal
Accurate Computation of Survival Statistics in Genome-Wide Studies. PLoS Comput. Biol. 11 (5) (2015)
Andrea Pietracaprina, Geppino Pucci, Francesco Silvestri, Fabio Vandin
Space-efficient parallel algorithms for combinatorial search problems. J. Parallel Distributed Comput. 76 (2015)
Mark D. M. Leiserson, Hsin-Ta Wu, Fabio Vandin, Benjamin J. Raphael
CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer. RECOMB (2015)
Benjamin J. Raphael, Fabio Vandin
Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data. J. Comput. Biol. 22 (6) (2015)
Matteo Riondato, Fabio Vandin
Finding the True Frequent Itemsets. SDM (2014)
Benjamin J. Raphael, Fabio Vandin
Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data. RECOMB (2014)
Fabio Vandin, Alexandra Papoutsaki, Benjamin J. Raphael, Eli Upfal
Genome-Wide Survival Analysis of Somatic Mutations in Cancer. RECOMB (2013)
Matteo Riondato, Fabio Vandin
Controlling False Positives in Frequent Itemsets Mining through the VC-Dimension CoRR (2013)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Identifying significant mutations in large cohorts of cancer genomes. ICCABS (2013)
Andrea Pietracaprina, Geppino Pucci, Francesco Silvestri, Fabio Vandin
Space-Efficient Parallel Algorithms for Combinatorial Search Problems. MFCS (2013)
Andrea Pietracaprina, Geppino Pucci, Francesco Silvestri, Fabio Vandin
Space-Efficient Parallel Algorithms for Combinatorial Search Problems. CoRR (2013)
Lu He, Fabio Vandin, Gopal Pandurangan, Chris Bailey-Kellogg
Ballast: A Ball-based Algorithm for Structural Motifs. J. Comput. Biol. 20 (2) (2013)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Workshop: Algorithms for discovery of mutated pathways in cancer. ICCABS (2012)
Fabio Vandin, Patrick Clay, Eli Upfal, Benjamin J. Raphael
Discovery of Mutated Subnetworks Associated with Clinical Data in Cancer. Pacific Symposium on Biocomputing (2012)
Aris Anagnostopoulos, Ravi Kumar, Mohammad Mahdian, Eli Upfal, Fabio Vandin
Algorithms on evolving graphs. ITCS (2012)
Lu He, Fabio Vandin, Gopal Pandurangan, Chris Bailey-Kellogg
Ballast: A Ball-Based Algorithm for Structural Motifs. RECOMB (2012)
Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets. J. ACM 59 (3) (2012)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Finding Driver Pathways in Cancer: Models and Algorithms. Algorithms Mol. Biol. 7 (2012)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Algorithms and Genome Sequencing: Identifying Driver Pathways in Cancer. Computer 45 (3) (2012)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Discovery of Mutated Driver Pathways in Cancer. RECOMB (2011)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Finding Driver Pathways in Cancer: Models and Algorithms. WABI (2011)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Algorithms for Detecting Significantly Mutated Pathways in Cancer. J. Comput. Biol. 18 (3) (2011)
Roberto Grossi, Andrea Pietracaprina, Nadia Pisanti, Geppino Pucci, Eli Upfal, Fabio Vandin
MADMX: A Strategy for Maximal Dense Motif Extraction. J. Comput. Biol. 18 (4) (2011)
Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets CoRR (2010)
Roberto Grossi, Andrea Pietracaprina, Nadia Pisanti, Geppino Pucci, Eli Upfal, Fabio Vandin
MADMX: A Novel Strategy for Maximal Dense Motif Extraction CoRR (2010)
Fabio Vandin, Eli Upfal, Benjamin J. Raphael
Algorithms for Detecting Significantly Mutated Pathways in Cancer. RECOMB (2010)
Andrea Pietracaprina, Matteo Riondato, Eli Upfal, Fabio Vandin
frequent itemsets through progressive sampling. Data Min. Knowl. Discov. 21 (2) (2010)
Andrea Pietracaprina, Matteo Riondato, Eli Upfal, Fabio Vandin
Mining Top-K Frequent Itemsets Through Progressive Sampling CoRR (2010)
Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin
An efficient rigorous approach for identifying statistically significant frequent itemsets. PODS (2009)
Roberto Grossi, Andrea Pietracaprina, Nadia Pisanti, Geppino Pucci, Eli Upfal, Fabio Vandin
MADMX: A Novel Strategy for Maximal Dense Motif Extraction. WABI (2009)
Andrea Pietracaprina, Fabio Vandin
Efficient Incremental Mining of Top-K Frequent Closed Itemsets. Discovery Science (2007)