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2020 – today
- 2024
[j30]Leonardo Pellegrina, Fabio Vandin:
Efficient Discovery of Significant Patterns with Few-Shot Resampling. Proc. VLDB Endow. 17(10): 2668-2680 (2024)- [j29]Leonardo Pellegrina
, Fabio Vandin:
SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds. ACM Trans. Knowl. Discov. Data 18(3): 52:1-52:55 (2024) - [c42]Leonardo Pellegrina, Fabio Vandin:
Scalable Rule Lists Learning with Sampling. KDD 2024: 2352-2363 - [c41]Ilie Sarpe, Fabio Vandin, Aristides Gionis:
Scalable Temporal Motif Densest Subnetwork Discovery. KDD 2024: 2536-2547 - [i20]Ilie Sarpe, Fabio Vandin, Aristides Gionis:
Scalable Temporal Motif Densest Subnetwork Discovery. CoRR abs/2406.10608 (2024) - [i19]Leonardo Pellegrina, Fabio Vandin:
Efficient Discovery of Significant Patterns with Few-Shot Resampling. CoRR abs/2406.11803 (2024) - [i18]Leonardo Pellegrina, Fabio Vandin:
Scalable Rule Lists Learning with Sampling. CoRR abs/2406.12803 (2024) - [i17]Cristian Boldrin, Fabio Vandin:
Fast and Accurate Triangle Counting in Graph Streams Using Predictions. CoRR abs/2409.15205 (2024) - 2023
- [j28]Andrea Tonon, Fabio Vandin:
caSPiTa: mining statistically significant paths in time series data from an unknown network. Knowl. Inf. Syst. 65(6): 2347-2374 (2023) - [c40]Paolo Pellizzoni, Fabio Vandin:
VC-dimension and Rademacher Averages of Subgraphs, with Applications to Graph Mining. ICDE 2023: 2470-2482 - [c39]Dario Simionato, Fabio Vandin:
Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages (Extended Abstract). IJCAI 2023: 6492-6497 - 2022
- [j27]Diego Santoro, Leonardo Pellegrina, Matteo Comin, Fabio Vandin:
SPRISS: approximating frequent k-mers by sampling reads, and applications. Bioinform. 38(13): 3343-3350 (2022) - [j26]Fabio Vandin:
Technical perspective: Evaluating sampled metrics is challenging. Commun. ACM 65(7): 74 (2022) - [j25]Davide Buffelli, Fabio Vandin:
The Impact of Global Structural Information in Graph Neural Networks Applications. Data 7(1): 10 (2022) - [j24]Andrea Tonon, Fabio Vandin:
gRosSo: mining statistically robust patterns from a sequence of datasets. Knowl. Inf. Syst. 64(9): 2329-2359 (2022) - [j23]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): 124:1-124:29 (2022) - [c38]Davide Buffelli, Fabio Vandin:
Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach. IJCNN 2022: 1-8 - [c37]Davide Buffelli, Pietro Lió, Fabio Vandin:
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. NeurIPS 2022 - [c36]Dario Simionato, Fabio Vandin:
Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages. ECML/PKDD (5) 2022: 255-271 - [i16]Davide Buffelli, Fabio Vandin:
Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach. CoRR abs/2201.03326 (2022) - [i15]Davide Buffelli, Pietro Liò, Fabio Vandin:
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. CoRR abs/2207.07888 (2022) - 2021
- [j22]Matteo Comin, Barbara Di Camillo, Cinzia Pizzi, Fabio Vandin:
Comparison of microbiome samples: methods and computational challenges. Briefings Bioinform. 22(1): 88-95 (2021) - [c35]Ilie Sarpe, Fabio Vandin:
odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks. CIKM 2021: 1568-1577 - [c34]Andrea Tonon, Fabio Vandin:
CASPITA: Mining Statistically Significant Paths in Time Series Data from an Unknown Network. ICDM 2021: 639-648 - [c33]Ilie Sarpe, Fabio Vandin:
PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts. SDM 2021: 145-153 - [c32]Federico Altieri, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin:
Scalable Distributed Approximation of Internal Measures for Clustering Evaluation. SDM 2021: 648-656 - [i14]Ilie Sarpe, Fabio Vandin:
PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts. CoRR abs/2101.07152 (2021) - [i13]Leonardo Pellegrina, Fabio Vandin:
SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds. CoRR abs/2106.03462 (2021) - [i12]Ilie Sarpe, Fabio Vandin:
odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks. CoRR abs/2108.08734 (2021) - 2020
- [j21]Diego Santoro, Andrea Tonon, Fabio Vandin:
Mining Sequential Patterns with VC-Dimension and Rademacher Complexity. Algorithms 13(5): 123 (2020) - [j20]Leonardo Pellegrina, Fabio Vandin:
Efficient mining of the most significant patterns with permutation testing. Data Min. Knowl. Discov. 34(4): 1201-1234 (2020) - [j19]Leonardo Pellegrina, Cinzia Pizzi, Fabio Vandin:
Fast Approximation of Frequent k-Mers and Applications to Metagenomics. J. Comput. Biol. 27(4): 534-549 (2020) - [j18]Matteo Riondato, Fabio Vandin:
MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. ACM Trans. Knowl. Discov. Data 14(5): 56:1-56:31 (2020) - [c31]Andrea Tonon, Fabio Vandin:
GRosSo: Mining Statistically Robust Patterns from a Sequence of Datasets. ICDM 2020: 551-560 - [c30]Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato:
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. KDD 2020: 2165-2174 - [i11]Federico Altieri, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin:
Scalable Distributed Approximation of Internal Measures for Clustering Evaluation. CoRR abs/2003.01430 (2020) - [i10]Davide Buffelli, Fabio Vandin:
Are Graph Convolutional Networks Fully Exploiting Graph Structure? CoRR abs/2006.03814 (2020) - [i9]Davide Buffelli, Fabio Vandin:
Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation. CoRR abs/2006.03820 (2020) - [i8]Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato:
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. CoRR abs/2006.09085 (2020) - [i7]Davide Buffelli, Fabio Vandin:
A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings. CoRR abs/2012.06755 (2020)
2010 – 2019
- 2019
- [j17]Morteza Chalabi Hajkarim, Eli Upfal, Fabio Vandin:
Differentially mutated subnetworks discovery. Algorithms Mol. Biol. 14(1): 10:1-10:11 (2019) - [j16]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): 17 (2019) - [j15]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) - [c29]Andrea Tonon, Fabio Vandin:
Permutation Strategies for Mining Significant Sequential Patterns. ICDM 2019: 1330-1335 - [c28]Leonardo Pellegrina, Matteo Riondato, Fabio Vandin:
SPuManTE: Significant Pattern Mining with Unconditional Testing. KDD 2019: 1528-1538 - [c27]Leonardo Pellegrina, Matteo Riondato, Fabio Vandin:
Hypothesis Testing and Statistically-sound Pattern Mining. KDD 2019: 3215-3216 - [c26]Leonardo Pellegrina, Cinzia Pizzi, Fabio Vandin:
Fast Approximation of Frequent k-mers and Applications to Metagenomics. RECOMB 2019: 208-226 - 2018
- [c25]Leonardo Pellegrina, Fabio Vandin:
Efficient Mining of the Most Significant Patterns with Permutation Testing. KDD 2018: 2070-2079 - [c24]Matteo Riondato, Fabio Vandin:
MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. KDD 2018: 2130-2139 - [c23]Rebecca Sarto Basso, Dorit S. Hochbaum, Fabio Vandin:
Efficient Algorithms to Discover Alterations with Complementary Functional Association in Cancer. RECOMB 2018: 278-279 - [c22]Morteza Chalabi Hajkarim, Eli Upfal, Fabio Vandin:
Differentially Mutated Subnetworks Discovery. WABI 2018: 18:1-18:14 - 2017
- [j14]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): 549-551 (2017) - [j13]Matteo Ceccarello, Carlo Fantozzi, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin:
Clustering Uncertain Graphs. Proc. VLDB Endow. 11(4): 472-484 (2017) - 2016
- [j12]Fabio Vandin, Benjamin J. Raphael, Eli Upfal:
On the Sample Complexity of Cancer Pathways Identification. J. Comput. Biol. 23(1): 30-41 (2016) - [j11]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) - [c21]Lorenzo De Stefani, Alessandro Epasto, Eli Upfal, Fabio Vandin:
Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic. AAAI 2016: 1526-1532 - [c20]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: 3-16 - [c19]Tommy Hansen, Fabio Vandin:
Finding Mutated Subnetworks Associated with Survival in Cancer. RECOMB 2016: 250 - [c18]Anna Bomersbach, Marco Chiarandini, Fabio Vandin:
An Efficient Branch and Cut Algorithm to Find Frequently Mutated Subnetworks in Cancer. WABI 2016: 27-39 - [i6]Matteo Ceccarello, Carlo Fantozzi, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin:
Clustering Uncertain Graphs. CoRR abs/1612.06675 (2016) - 2015
- [j10]Benjamin J. Raphael, Fabio Vandin:
Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data. J. Comput. Biol. 22(6): 510-527 (2015) - [j9]Andrea Pietracaprina, Geppino Pucci, Francesco Silvestri, Fabio Vandin:
Space-efficient parallel algorithms for combinatorial search problems. J. Parallel Distributed Comput. 76: 58-65 (2015) - [j8]Fabio Vandin, Alexandra Papoutsaki, Benjamin J. Raphael, Eli Upfal:
Accurate Computation of Survival Statistics in Genome-Wide Studies. PLoS Comput. Biol. 11(5) (2015) - [c17]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: 202-204 - [c16]Fabio Vandin, Benjamin J. Raphael, Eli Upfal:
On the Sample Complexity of Cancer Pathways Identification. RECOMB 2015: 326-337 - 2014
- [c15]Benjamin J. Raphael, Fabio Vandin:
Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data. RECOMB 2014: 250-264 - [c14]Matteo Riondato, Fabio Vandin:
Finding the True Frequent Itemsets. SDM 2014: 497-505 - 2013
- [j7]Lu He, Fabio Vandin, Gopal Pandurangan, Chris Bailey-Kellogg:
Ballast: A Ball-based Algorithm for Structural Motifs. J. Comput. Biol. 20(2): 137-151 (2013) - [c13]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Identifying significant mutations in large cohorts of cancer genomes. ICCABS 2013: 1 - [c12]Andrea Pietracaprina, Geppino Pucci, Francesco Silvestri, Fabio Vandin:
Space-Efficient Parallel Algorithms for Combinatorial Search Problems. MFCS 2013: 717-728 - [c11]Fabio Vandin, Alexandra Papoutsaki, Benjamin J. Raphael, Eli Upfal:
Genome-Wide Survival Analysis of Somatic Mutations in Cancer. RECOMB 2013: 285-286 - [i5]Matteo Riondato, Fabio Vandin:
Controlling False Positives in Frequent Itemsets Mining through the VC-Dimension. CoRR abs/1301.1218 (2013) - [i4]Andrea Pietracaprina, Geppino Pucci, Francesco Silvestri, Fabio Vandin:
Space-Efficient Parallel Algorithms for Combinatorial Search Problems. CoRR abs/1306.2552 (2013) - 2012
- [j6]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Finding Driver Pathways in Cancer: Models and Algorithms. Algorithms Mol. Biol. 7: 23 (2012) - [j5]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Algorithms and Genome Sequencing: Identifying Driver Pathways in Cancer. Computer 45(3): 39-46 (2012) - [j4]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): 12:1-12:22 (2012) - [c10]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Workshop: Algorithms for discovery of mutated pathways in cancer. ICCABS 2012: 1 - [c9]Aris Anagnostopoulos, Ravi Kumar, Mohammad Mahdian, Eli Upfal, Fabio Vandin:
Algorithms on evolving graphs. ITCS 2012: 149-160 - [c8]Fabio Vandin, Patrick Clay, Eli Upfal, Benjamin J. Raphael:
Discovery of Mutated Subnetworks Associated with Clinical Data in Cancer. Pacific Symposium on Biocomputing 2012: 55-66 - [c7]Lu He, Fabio Vandin, Gopal Pandurangan, Chris Bailey-Kellogg:
Ballast: A Ball-Based Algorithm for Structural Motifs. RECOMB 2012: 79-93 - 2011
- [j3]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Algorithms for Detecting Significantly Mutated Pathways in Cancer. J. Comput. Biol. 18(3): 507-522 (2011) - [j2]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): 535-545 (2011) - [c6]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
De Novo Discovery of Mutated Driver Pathways in Cancer. RECOMB 2011: 499-500 - [c5]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Finding Driver Pathways in Cancer: Models and Algorithms. WABI 2011: 314-325 - 2010
- [j1]Andrea Pietracaprina, Matteo Riondato, Eli Upfal, Fabio Vandin:
Mining top-K frequent itemsets through progressive sampling. Data Min. Knowl. Discov. 21(2): 310-326 (2010) - [c4]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Algorithms for Detecting Significantly Mutated Pathways in Cancer. RECOMB 2010: 506-521 - [i3]Roberto Grossi, Andrea Pietracaprina, Nadia Pisanti, Geppino Pucci, Eli Upfal, Fabio Vandin:
MADMX: A Novel Strategy for Maximal Dense Motif Extraction. CoRR abs/1002.0874 (2010) - [i2]Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin:
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets. CoRR abs/1002.1104 (2010) - [i1]Andrea Pietracaprina, Matteo Riondato, Eli Upfal, Fabio Vandin:
Mining Top-K Frequent Itemsets Through Progressive Sampling. CoRR abs/1006.5235 (2010)
2000 – 2009
- 2009
- [c3]Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin:
An efficient rigorous approach for identifying statistically significant frequent itemsets. PODS 2009: 117-126 - [c2]Roberto Grossi, Andrea Pietracaprina, Nadia Pisanti, Geppino Pucci, Eli Upfal, Fabio Vandin:
MADMX: A Novel Strategy for Maximal Dense Motif Extraction. WABI 2009: 362-374 - 2007
- [c1]Andrea Pietracaprina, Fabio Vandin:
Efficient Incremental Mining of Top-K Frequent Closed Itemsets. Discovery Science 2007: 275-280
Coauthor Index
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last updated on 2024-10-16 21:22 CEST by the dblp team
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