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Publications

2023

Conferences

• P. Pellizzoni, F. Vandin. VC-dimension and Rademacher Averages of Subgraphs, with Applications to Graph Mining. In 39th IEEE International Conference on Data Engineering (ICDE)

Journals

• A. Tonon, F. Vandin. caSPiTa: mining statistically significant paths in time series data from an unknown network. Knowledge and Information Systems, 65(6), 2347-2374.

2022

Conferences

• D. Buffelli, F. Vandin. Graph representation learning for multi-task settings: a meta-learning ap- proach In 2022 IEEE International Joint Conference on Neural Networks (IJCNN), 2022
• D. Simionato, F. Vandin. Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages. In Machine Learning and Knowledge Discovery in Databases: European Conference (ECML PKDD), 2022.
• D. Buffelli, P. Lio`, F. Vandin. Sizeshiftreg: a regularization method for improving size-generalization in graph neural networks. In Advances in Neural Information Processing Systems (NeurIPS), 2022.

Journals

• D. Buffelli, F. Vandin. The impact of global structural information in graph neural networks applications. Data, 7(1), 10 (2022).
• F. Vandin. Technical perspective: Evaluating sampled metrics is challenging. Communications of the ACM, 65(7), 74 (2022).
• D. Santoro, L. Pellegrina, M. Comin, F. Vandin. SPRISS: approximating frequent k-mers by sampling reads, and applications. Bioinformatics, 38(13), 3343-3350 (2022).
• L. Pellegrina, C. Cousins, F. Vandin, M. Riondato. MCRapper: Monte-Carlo Rademacher averages for poset families and approximate pattern mining. ACM Transactions on Knowledge Discovery from Data, 16(6), 1-29 (2022).
• A. Tonon, F. Vandin. gRosSo: mining statistically robust patterns from a sequence of datasets. Knowledge and Information Systems, 64(9), 2329-2359 (2022).
• L. Pellegrina, F. Vandin. Discovering significant evolutionary trajectories in cancer phylogenies. Bioinformatics, 38(Supplement 2), ii49-ii55 (2022).

2021

Conferences

• F. Altieri, A. Pietracaprina, G. Pucci, F. Vandin. Scalable distributed approximation of internal measures for clustering evaluation. In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), pages 648-656, 2021.
• I. Sarpe, F. Vandin. PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts. In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM)
• D. Santoro†, L. Pellegrina†, F. Vandin. SPRISS: Approximating Frequent k-mers by Sampling Reads, and Applications. 25th Annual International Conference on Research in Computational Molecular Biology (RECOMB)
• I. Sarpe, F. Vandin. odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks. 30th ACM International Conference on Information and Knowledge Management (CIKM)
• A. Tonon, F. Vandin. CASPITA: Mining Statistically Significant Paths in Time Series Data from an Unknown Network. 21st IEEE International Conference on Data Mining (ICDM)

Journals

• D. Buffelli, F. Vandin. Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation. IEEE Sensors Journal (2021).

2020

Conferences

• L. Pellegrina, C. Cousins, F. Vandin, M. Riondato. MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. 26th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD)
• A. Tonon, F. Vandin. GRosSo: Mining Statistically Robust Patterns from a Sequence of Datasets. In 2020 IEEE International Conference on Data Mining (ICDM)

Journals

• L. Pellegrina, C. Pizzi, and F. Vandin. Fast Approximation of Frequent k-mers and Applications to Metagenomics. Journal of Computational Biology, 27 (4), 534-549 (2020).
• M. Riondato, F. Vandin. MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodi- mension. ACM Transactions on Knowledge Discovery from Data, 14 (5), 1-31 (2020)
• L. Pellegrina, F. Vandin. Efficient Mining of the Most Significant Patterns with Permutation Testing. Data Mining and Knowledge Discovery, 34, 1201-1234 (2020)
• D. Santoro, A. Tonon, F. Vandin. Mining Sequential Patterns with VC-Dimension and Rademacher Complexity. Algorithms, 13, 123 (2020).
• M. Comin, B. Di Camillo, C. Pizzi, F. Vandin. Comparison of microbiome samples: methods and computational challenges. Briefings in Bioinformatics, bbaa121 (2020).
• Y.-A. Kim, D. Wojtowicz, R. Sarto Basso, I. Sason, W. Robinson, D. S. Hochbaum, M. DM Leiserson, R. Sharan, F. Vandin, T. M. Przytycka. Network-based approaches elucidate differences within APOBEC and clock-like signatures in breast cancer. Genome Medicine, 12, 1-12 (2020).
• Y.-A. Kim, R. Sarto Basso, , D. Wojtowicz,, A. S. Liu, D. S. Hochbaum, F. Vandin, T. M. Przytycka. Identifying drug sensitivity subnetworks with netphix . Iscience, 23(10), 101619 (2020).

2019

Conferences

• L. Pellegrina, M. Riondato, and F. Vandin. SPuManTE: Significant Pattern Mining with Unconditional Testing. Accepted at 25th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD).
• L. Pellegrina, C. Pizzi, and F. Vandin. Fast Approximation of Frequent k-mers and Applications to Metagenomics. Accepted at 23rd Annual International Conference on Research in Computational Molecular Biology (RECOMB).

Journals

• R. Sarto Basso, D. Hochbaum, and F. Vandin. Efficient Algorithms to Discover Alterations with Complementary Functional Association in Cancer. PLOS Computational Biology, in press.
• M. H. Chalabi, V. Tsiamis, L. Käll, F. Vandin, V. Schwämmle. CoExpresso: assess the quantitative behavior of protein complexes in human cells. BMC bioinformatics 20 (1), 17.
• F. Altieri, T. V. Hansen, F. Vandin. NoMAS: A Computational Approach to Find Mutated Subnetworks Associated with Survival in Genome-Wide Cancer Studies. Frontiers in Genetics 10, 265.
• M. C. Hajkarim, E. Upfal, F. Vandin. Differentially mutated subnetworks discovery. Algorithms for Molecular Biology 14 (1), 10.
• W. Li, J. Baumbach, A. Mohammadnejad, C. Brasch-Andersen, F. Vandin, J. O. Korbel, Q. Tan.Enriched power of disease-concordant twin-case-only design in detecting interactions in genome-wide association studies. European Journal of Human Genetics, 27, 631–636.

2018

Conferences

• L. Pellegrina and F. Vandin. Efficient Mining of the Most Significant Patterns with Permutation Testing. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).
• M. Riondato and F. Vandin. MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).
• Morteza Chalabi Hajkarim, Eli Upfal, and Fabio Vandin. Differentially Mutated Subnetworks Discovery. 18th Workshop on Algorithms in Bioinformatics (WABI).
• R. Sarto Basso, D. Hochbaum, and F. Vandin. Efficient Algorithms to Discover Alterations with Complementary Functional Association in Cancer. 22nd Annual International Conference on Research in Computational Molecular Biology (RECOMB).

2017

Journals

• Matteo Ceccarello, Carlo Fantozzi, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin. Clustering Uncertain Graph PVLDB, 4 (11):472-484.
• Vandin F. Computational Methods for Characterizing Cancer Mutational Heterogeneity. Frontiers in genetics, 8.
• Raunak Shrestha, Ermin Hodzic, Thomas Sauerwald, Phuong Dao, Kendric Wang, Jake Yeung, Shawn Anderson, Fabio Vandin, Gholamreza Haffari, Colin C Collins, S Cenk Sahinalp. HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology. Genome Research, 27 (9), 1573-1588.
• N Alcaraz, M List, R Batra, F Vandin, HJ Ditzel, J Baumbach. De novo pathway-based biomarker identification Nucleic Acids Research.
• Diogo Almeida, Ida Skov, Artur Silva, Fabio Vandin, Qihua Tan, Richard Röttger, Jan Baumbach. Efficient detection of differentially methylated regions using DiMmeR Bioinformatics, Volume 33, Issue 4, 15 February 2017, Pages 549–551
• Q Tan, W Li, F Vandin. Disease‐Concordant Twins Empower Genetic Association Studies. Annals of human genetics 81 (1), 20-26.

Conferences

• W Li, F Vandin, J Baumbach, Q Tan. Enriched power of case-only design in detecting gene-gene interaction using disease concordant twins. (Poster) International Symposium on Integrative Bioinformatics, 2017.

2016

Journals

• Vandin, F, Raphael, BJ, Upfal, E. On the Sample Complexity of Cancer Pathways Identification. Journal of Computational Biology, 23, 1:30-41 (2016).
  publisher link
• The Computational Pan-Genomics Consortium. Computational pan-genomics: status, promises and challenges. Briefings in Bioinformatics, bbw089 (2016).
• Chen M., Baumbach J., Vandin F., Röttgr R., Barbosa E., Dong M., Frost ., Christiansen L., Tan Q. Differentially Methylated Genomic Regions in Birth-Weight Discordant Twin Pairs. Annals of Human Genetics (2016).
  publisher link
• 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 Infinium MethylationEPIC BeadChip data processing Journal of Integrative Bioinformatics 13 (4), 24-32.

Conferences

• Tommy Hansen and Fabio Vandin. Finding Mutated Subnetworks Associated with Survival Time in Cancer. RECOMB 2016
• 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
• Lorenzo De Stefani, Alessandro Epasto, Eli Upfal, Fabio Vandin. Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic. AAAI 2016
• Bomersbach, A, Chiarandini, M., Vandin, F. An Efficient Branch and Cut Algorithm to Find Frequently Mutated Subnetworks in Cancer. WABI, 2016.

2015

Journals

• Mark Leiserson, Hsin-Ta Wu, Fabio Vandin and Benjamin Raphael. CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer. Genome Biology, 16:160 (2015).
• M. D.M. Leiserson*, F. Vandin*, H.-T. Wu, J. R. Dobson, J. V. Eldridge, J. L. Thomas, A. Papoutsaki, Y. Kim, B. Niu, M. McLellan, M. S. Lawrence, A. Gonzalez-Perez, D. Tamborero, Y. Cheng, G. A. Ryslik, N. Lopez-Bigas, G. Getz, L. Ding, B. J. Raphael. Pan-Cancer Network Analysis Identifies Combinations of Rare Somatic Mutations across Pathways and Protein Complexes. Nature Genetics 47, 106-114 (2015).
  publisher link
  website
  software
• F. Vandin, A. Papoutsaki, B. J. Raphael, E. Upfal. Accurate Computation of Survival Statistics in Genome-wide Studies. PLoS Comput Biol 11(5): e1004071. doi: 10.1371/journal.pcbi.1004071.
  publisher link
• B. J. Raphael and F. Vandin. Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data. Accepted for publication in Journal of Computational Biology. June 2015, 22(6): 510-527. doi:10.1089/cmb.2014.0161.
  publisher link
• Space-Efficient Parallel Algorithms for Combinatorial Search Problems, A. Pietracaprina, G. Pucci, F. Silvestri, and F. Vandin. Journal of Parallel and Distributed Computing., Volume 76, February 2015, Pages 58-65.
  publisher link

Conferences

• Mark Leiserson, Hsin-Ta Wu, Fabio Vandin and Benjamin Raphael. CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer. 19th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2015.
• Fabio Vandin, Ben Raphael and Eli Upfal. On the Sample Complexity of Cancer Pathways Identification. 19th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2015.

2014

Journals

• B.J. Raphael, J.R. Dobson, L. Oesper, and F. Vandin. Identifying driver mutations in sequenced cancer genomes: computational approaches to enable precision medicine. Genome Medicine, 2014, 6:5.
  publisher link
• Hoadley K. A., Yau C., Wolf D. M., Cherniack A. D., Tamborero D., Ng S., Leiserson M. D., Niu B., McLellan M. D. , Uzunangelov V., Zhang J., Kandoth C., Akbani R., Shen H., Omberg L., Chu A., Margolin A. A., Van't Veer L. J., Lopez-Bigas N., Laird P. W., Raphael B. J., Ding L., Robertson A. G., Byers L. A., Mills G. B., Weinstein J. N., Van Waes C., Chen Z., Collisson E. A., The Cancer Genome Atlas Research Network, Benz C. C., Perou C. M., Stuart J. M. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell, 158 (4), 929-944 (2014).
  publisher link
• The Cancer Genome Atlas Research Network.Integrated Genomic Characterization of Papillary Thyroid Carcinoma. Cell, 159 (3), 676 - 690 (2014).
  publisher link

Conferences

• B.J. Raphael, F. Vandin. Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data. In Proceedings 18th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2014, pages 250-264, 2014.
  publisher link
• M. Riondato, F. Vandin. Finding the True Frequent Itemsets. In Proceedings SIAM International Conference on Data Mining (SDM), pages 497-505, 2014.
  publisher link
• F. Vandin, and B. Raphael. Reconstructing Cancer Pathways and Their Mutation Order from Cross-Sectional Data. ISMB 2014 (Abstract), Boston, USA, 2014
• M. D. Leiserson, F. Vandin, H. T. Wu, J. R. Dobson, and B. Raphael. Pan-cancer identification of mutated pathways and protein complexes. Cancer Research (Abstract), 74(19) 5324-5324, 2014.

2013

Journals

• L. He, F. Vandin, G. Pandurangan, and C. Bailey-Kellogg. BALLAST: A Ball-based Algorithm for Structural Motifs. Journal of Computational Biologyi, 20(2): 137-151 (2013).
• The Cancer Genome Atlas Research Network. Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia. New England Journal of Medicine , May 1st 2013.
  publisher link
• The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature, 2013 Jul 4; 499(7456):43-9.
  publisher link
• The Cancer Genome Atlas Research Network. The Cancer Genome Atlas Pan-Cancer analysis project. Nature Genetics, 2013, 45(10):1113-20.
  publisher link
• C.Kandoth*, M.D. McLellan*, F. Vandin, K.Ye, B. Niu, C. Lu, M. Xie, Q. Zhang, J.F. McMichael, M.A. Wyczalkowski, M.D.M. Leiserson, C.A. Miller, J.S. Welch, M.J. Walter, M.C. Wendl, T.J. Ley, R.K. Wilson, B.J. Raphael, L. Ding. Mutational landscape and significance across 12 major cancer types. Nature, 2013, 502, 333-339.
  publisher link

Conferences

• F. Vandin, A. Papoutsaki, B. Raphael, and E. Upfal. Genome-Wide Survival Analysis of Somatic Mutations in Cancer. In Proceedings 17th International Conference on Research in Computational Molecular Biology (RECOMB), LNCS 7821, 2013, pp 285-286.
  Best Paper Award
  publisher link
  software
• A. Pietracaprina, G. Pucci, F. Silvestri, F. Vandin. Space-Efficient Parallel Algorithms for Combinatorial Search Problems. In Proceedings 38th International Symposium on Mathematical Foundations of Computer Science (MFCS), 2013, accepted for publication.
  full version on Arxiv (with omitted proofs)
• M. Leiserson, H.-T. Wu, F. Vandin and B. J. Raphael. Network analysis of mutations across cancer types. (Poster) 17th International Conference on Research in Computational Molecular Biology (RECOMB), (Poster/Abstract) Beijing, China, 2013.
• F. Vandin, A. Papoutsaki, B. Raphael, and E. Upfal. Accurate Genome-Wide Survival Analysis of Somatic Mutations in Cancer. (Poster) ISMB ECCB 2013, Berlin, Germany, 2013.

2012

Journals

• F. Vandin, E. Upfal, and B. J. Raphael. De novo Discovery of Mutated Driver Pathways in Cancer. Genome Research 22(2):375-85, 2012. Epub 2011 Jun 7.
  pdf preprint
  publisher link
  software
• F. Vandin, E. Upfal, B.J. Raphael. Algorithms and Genome Sequencing: Identifying Driver Pathways in Cancer. IEEE Computer, March 2012 (vol. 45, no. 3) pp.39-46.
  pdf
• A. Kirsch, M. Mitzenmacher, A. Pietracaprina, G. Pucci, E. Upfal, and F. Vandin. An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets. Journal of the ACM. 59(3):12:1-12:22.
• C. Grasso , Y.Wu , D. Robinson , X. Cao , S. Dhanasekaran , A. Khan , M. Quist , X. Jing , R. Lonigro , J.C. Brenner , I. Asangani , B. Ateeq , S. Chun , J. Siddiqui , L. Sam , M. Anstett , R. Mehra , J. Prensner , N. Palanisamy , G. Ryslik , F. Vandin , B. Raphael , L. Kunju , D. Rhodes , K. Pienta , A. M. Chinnaiyan, S.A. Tomlins. The Mutational Landscape of Lethal Castrate Resistant Prostate Cancer. Nature, 2012 Jul 12;487(7406):239-43.
  publisher link
• F. Vandin, E. Upfal, and B. J. Raphael. Finding Driver Pathways in Cancer: Models and Algorithms. Algorithms for Molecular Biology, 2012 Sep 6;7(1):23.

Conferences

• F. Vandin, P. Clay, E. Upfal, and B. J. Raphael. Discovery of Mutated Subnetworks Associated with Clinical Data in Cancer. In Proc. Pacific Symposium on Biocomputing (PSB), 2012.
  pdf
  software
• A. Anagnostopoulos, R. Kumar, M. Mahdian, E. Upfal, and F. Vandin. Algorithms on Evolving Graphs. In Proc. of 3rd Innovations in Theoretical Computer Science (ITCS), pages 149-160, 2012.
  pdf
  publisher link
• L. He, F. Vandin, G. Pandurangan, and C. Bailey-Kellogg. Ballast: A Ball-based Algorithm for Structural Motifs. In Proc. 16th International Conference on Research in Computational Molecular Biology (RECOMB), LNCS 7262, pages 79-93, 2012.
  publisher link
• F. Vandin, E. Upfal, and B. J. Raphael. Algorithms for Discovery of Mutated Pathways in Cancer. (Abstract) 2nd Workshop on Computational Advances for Next Generation Sequencing (CANGS) 2012, Las Vegas, NV, 2012.
• F. Vandin, H-T. Wu, E. Upfal, and B. J. Raphael. Algorithms to Find Mutated Pathways in Cancer. 16th International Conference on Research in Computational Molecular Biology (RECOMB) 2012, (Poster/Abstract) Barcelona, Spain, 2012.
• M. Leiserson, H.-T. Wu, D. Blokh, F. Vandin, R. Sharan, B. J. Raphael. Methods for Identifying Driver Pathways in Cancer. (Poster) 3rd Annual Beyond the Genome Conference, Boston, USA, 2012.
• Leiserson, H.-T. Wu,A. Deschamps, F. Vandin, and B. J. Raphael. Pathway and Network Analysis of Somatic Mutations Across Cancer Types in TCGA (Poster/Abstract) The Cancer Genome Atlas' 2nd Annual Scientific Symposium, Washington DC, 2012.

2011

Journals

• F. Vandin, E. Upfal, and B. J. Raphael. Algorithms for Detecting Significantly Mutated Pathways in Cancer. Journal of Computational Biology, March 2011, 18(3): 507-522.
  pdf
  software
• R. Grossi, A. Pietracaprina, N. Pisanti, G. Pucci, E. Upfal, and F. Vandin. MADMX: A Strategy for Maximal Dense Motif Extraction. Journal of Computational Biology, April 2011, 18(4): 535-545.
  pdf
  software
• The Cancer Genome Atlas Project Research Network. Integrated Genomic Analyses of Ovarian Carcinoma. Nature, 2011 Jun. 30;474(7353):609-15.
  publisher link

Conferences

• F. Vandin, E. Upfal, and B. J. Raphael. De novo Discovery of Mutated Driver Pathways in Cancer. In Proc. 15th International Conference on Research in Computational Molecular Biology (RECOMB), LNCS 6577, pages 499-500, 2011.
  pdf
  software
• F. Vandin, E. Upfal, and B. J. Raphael. Finding Driver Pathways in Cancer: Models and Algorithms. In Proc. 11th Workshop on Algorithms in Bioinformatics (WABI 2011), LNCS 6833, pages 314-325.
  pdf
• L. He, F. Vandin, G. Pandurangan, and C. Bailey-Kellogg. Ball-based Algorithms for Structural Motifs. (Poster) 3DSIG 2011, Structural Bioinformatics and Computational Biophysics, ISMB Satellite Meeting, Vienna (Austria), 2011.
• F. Vandin, H-T. Wu, E. Upfal, and B. J. Raphael. Algorithms for Automated Discovery of Mutated Pathways in Cancer. (Poster/Abstract) The Cancer Genome Atlas' 1st Annual Scientific Symposium, Washington DC, 2011.

2007-2010

• F. Vandin, E. Upfal, and B. J. Raphael. Algorithms for Detecting Significantly Mutated Pathways in Cancer. In Proc. 14th International Conference on Research in Computational Molecular Biology (RECOMB) 2010, LNCS 6044, pages 506-521, Lisbon (Portugal), 2010.
  pdf
  software
• A. Pietracaprina, M. Riondato, E. Upfal, F. Vandin. Mining Top-K Frequent Itemsets Through Progressive Sampling. Data Mining and Knowledge Discovery, ECML PKDD 2010 special issue, Volume 21, Number 2, 2010.
  pdf
• F. Vandin, E. Upfal, and B. J. Raphael. Detection of Mutated Pathways in Cancer. (Poster) 18th International Conference on Intelligent Systems for Molecular Biology (ISMB) 2010, Boston, MA, 2010.
• A. Kirsch, M. Mitzenmacher, A. Pietracaprina, G. Pucci, E. Upfal, and F. Vandin. An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets. In Proc. of 28th ACM Symposium on Principles of Database Systems (PODS'09), pages 117-226, 2009.
  pdf
• R. Grossi, A. Pietracaprina, N. Pisanti, G. Pucci, E. Upfal, and F. Vandin. MADMX: A Novel Strategy for Maximal Dense Motif Extraction. In Proc. 9th Workshop on Algorithms in Bioinformatics, (WABI 2009), LNCS 5724, pages 362-374.
  pdf
  software
• F. Vandin, E. Upfal, and B. J. Raphael. Identification of Significantly Mutated Pathways in Cancer. (Abstract) Annual RECOMB Satellite 2009 MIT, Boston, MA, December 2009.
• A. Pietracaprina, and F. Vandin. Efficient Incremental Mining of Top-K Frequent Closed Itemsets. In Proc. International Conference on Discovery Science (DS) 2007, LNCS 4755, pages 275-280, 2007.
  pdf

Theses

• Laurea Triennale Final Project: "Models and Methods for the Evaluation of Runway Capacity", Advisor: Prof. Lorenzo Brunetta. University of Padova, 2004
• Laurea Specialistica Thesis: "On the Top-K Frequent Closed Itemsets Mining Problem", Advisors: Prof. Andrea Pietracaprina, Prof. Geppino Pucci. University of Padova, 2006 (officially deemed as distinguished by the thesis committee)
• Ph.D. Thesis: "Mining Significant Patterns: Theory and Practice", Advisor: Prof. Andrea Pietracaprina. University of Padova, 2010. pdf

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