Fabio Vandin

Orcid: 0000-0003-2244-2320

According to our database1, Fabio Vandin authored at least 59 papers between 2007 and 2024.

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Bibliography

2024
SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds.
ACM Trans. Knowl. Discov. Data, April, 2024

2023
caSPiTa: mining statistically significant paths in time series data from an unknown network.
Knowl. Inf. Syst., June, 2023

Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

VC-dimension and Rademacher Averages of Subgraphs, with Applications to Graph Mining.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining.
ACM Trans. Knowl. Discov. Data, 2022

gRosSo: mining statistically robust patterns from a sequence of datasets.
Knowl. Inf. Syst., 2022

The Impact of Global Structural Information in Graph Neural Networks Applications.
Data, 2022

Technical perspective: Evaluating sampled metrics is challenging.
Commun. ACM, 2022

SPRISS: approximating frequent <i>k</i>-mers by sampling reads, and applications.
Bioinform., 2022

Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach.
Proceedings of the International Joint Conference on Neural Networks, 2022

2021
Comparison of microbiome samples: methods and computational challenges.
Briefings Bioinform., 2021

PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Scalable Distributed Approximation of Internal Measures for Clustering Evaluation.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension.
ACM Trans. Knowl. Discov. Data, 2020

Fast Approximation of Frequent k-Mers and Applications to Metagenomics.
J. Comput. Biol., 2020

Efficient mining of the most significant patterns with permutation testing.
Data Min. Knowl. Discov., 2020

A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings.
CoRR, 2020

Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation.
CoRR, 2020

Are Graph Convolutional Networks Fully Exploiting Graph Structure?
CoRR, 2020

Mining Sequential Patterns with VC-Dimension and Rademacher Complexity.
Algorithms, 2020

2019
CoExpresso: assess the quantitative behavior of protein complexes in human cells.
BMC Bioinform., December, 2019

Efficient algorithms to discover alterations with complementary functional association in cancer.
PLoS Comput. Biol., 2019

Differentially mutated subnetworks discovery.
Algorithms Mol. Biol., 2019

Hypothesis Testing and Statistically-sound Pattern Mining.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

SPuManTE: Significant Pattern Mining with Unconditional Testing.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Permutation Strategies for Mining Significant Sequential Patterns.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2017
Clustering Uncertain Graphs.
Proc. VLDB Endow., 2017

Efficient detection of differentially methylated regions using DiMmeR.
Bioinform., 2017

2016
Jllumina - A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and MethylationEPIC data processing.
J. Integr. Bioinform., 2016

On the Sample Complexity of Cancer Pathways Identification.
J. Comput. Biol., 2016

An Efficient Branch and Cut Algorithm to Find Frequently Mutated Subnetworks in Cancer.
Proceedings of the Algorithms in Bioinformatics - 16th International Workshop, 2016

The Second Decade of the International Conference on Research in Computational Molecular Biology (RECOMB).
Proceedings of the Research in Computational Molecular Biology - 20th Annual Conference, 2016

Finding Mutated Subnetworks Associated with Survival in Cancer.
Proceedings of the Research in Computational Molecular Biology - 20th Annual Conference, 2016

Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Accurate Computation of Survival Statistics in Genome-Wide Studies.
PLoS Comput. Biol., 2015

Space-efficient parallel algorithms for combinatorial search problems.
J. Parallel Distributed Comput., 2015

Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data.
J. Comput. Biol., 2015

CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer.
Proceedings of the Research in Computational Molecular Biology, 2015

2014
Finding the True Frequent Itemsets.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

2013
Ballast: A Ball-based Algorithm for Structural Motifs.
J. Comput. Biol., 2013

Controlling False Positives in Frequent Itemsets Mining through the VC-Dimension
CoRR, 2013

Genome-Wide Survival Analysis of Somatic Mutations in Cancer.
Proceedings of the Research in Computational Molecular Biology, 2013

Identifying significant mutations in large cohorts of cancer genomes.
Proceedings of the IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences, 2013

2012
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets.
J. ACM, 2012

Algorithms and Genome Sequencing: Identifying Driver Pathways in Cancer.
Computer, 2012

Finding Driver Pathways in Cancer: Models and Algorithms.
Algorithms Mol. Biol., 2012

Discovery of Mutated Subnetworks Associated with Clinical Data in Cancer.
Proceedings of the Biocomputing 2012: Proceedings of the Pacific Symposium, 2012

Algorithms on evolving graphs.
Proceedings of the Innovations in Theoretical Computer Science 2012, 2012

Workshop: Algorithms for discovery of mutated pathways in cancer.
Proceedings of the IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, 2012

2011
Algorithms for Detecting Significantly Mutated Pathways in Cancer.
J. Comput. Biol., 2011

MADMX: A Strategy for Maximal Dense Motif Extraction.
J. Comput. Biol., 2011

<i>De Novo</i> Discovery of Mutated Driver Pathways in Cancer.
Proceedings of the Research in Computational Molecular Biology, 2011

2010
Mining top-<i>K</i> frequent itemsets through progressive sampling.
Data Min. Knowl. Discov., 2010

Mining Top-K Frequent Itemsets Through Progressive Sampling
CoRR, 2010

2009
MADMX: A Novel Strategy for Maximal Dense Motif Extraction.
Proceedings of the Algorithms in Bioinformatics, 9th International Workshop, 2009

2007
Efficient Incremental Mining of Top-K Frequent Closed Itemsets.
Proceedings of the Discovery Science, 10th International Conference, 2007


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