Simone Romano - Google Scholar

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	All	Since 2015
Citations	310	309
h-index	9	9
i10-index	8	8

20152016201720182019202018 40 47 71 71 62

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James BaileyProfessor, School of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Vinh NguyenDeep Learning @NVIDIAVerified email at nvidia.com
Jeffrey ChanSchool of Science (Computer Science and Software Engineering), RMIT UniversityVerified email at rmit.edu.au
Karin VerspoorProfessor, School of Computing and Information Systems; The University of MelbourneVerified email at unimelb.edu.au
James C. BezdekUniversity of Melbourne, Computer and Information SystemsVerified email at unimelb.edu.au
Christopher LeckieProfessor, Computing and Information Systems, The University of MelbourneVerified email at unimelb.edu.au
Jian PeiProfessor of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
Yisen WangGraduate from Tsinghua UniversityVerified email at mails.tsinghua.edu.cn
Xingjun MaLecturer@Deakin University, Honorary@University of MelbourneVerified email at unimelb.edu.au
Michael E. HouleNational Institute of Informatics, JapanVerified email at nii.ac.jp
Oussama ChellyMicrosoft AI & IoT Insider Lab EuropeVerified email at microsoft.com
Shu-Tao XiaTsinghua UniversityVerified email at sz.tsinghua.edu.cn
Lawrence CavedonComputer Science and IT, RMIT UniversityVerified email at rmit.edu.au
Orla MorrisseyAlfred Health and Monash UniversityVerified email at monash.edu
Sarah M. ErfaniSenior Lecturer, Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Hanxun HuangThe University of MelbourneVerified email at student.unimelb.edu.au
Prof R KotagiriProfessor, Computing and Information Systems, The University of Melbourne 1980-2020Verified email at unimelb.edu.au

Simone Romano

X-Scientist at Huawei, X-Applied Scientist at Microsoft, X-Researcher at NII Tokyo, PhD from

Verified email at simoneromano.com - Homepage

Machine Learning Artificial Intelligence Deep learning Data Mining


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Effective global approaches for mutual information based feature selection XV Nguyen, J Chan, S Romano, J Bailey Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	89	2014
Adjusting for chance clustering comparison measures S Romano, NX Vinh, J Bailey, K Verspoor The Journal of Machine Learning Research 17 (1), 4635-4666, 2016	52	2016
Standardized mutual information for clustering comparisons: one step further in adjustment for chance S Romano, J Bailey, V Nguyen, K Verspoor International Conference on Machine Learning, 1143-1151, 2014	51	2014
Discovering outlying aspects in large datasets NX Vinh, J Chan, S Romano, J Bailey, C Leckie, K Ramamohanarao, ... Data mining and knowledge discovery 30 (6), 1520-1555, 2016	33	2016
Extending information-theoretic validity indices for fuzzy clustering Y Lei, JC Bezdek, J Chan, NX Vinh, S Romano, J Bailey IEEE Transactions on Fuzzy Systems 25 (4), 1013-1018, 2016	22	2016
Ground truth bias in external cluster validity indices Y Lei, JC Bezdek, S Romano, NX Vinh, J Chan, J Bailey Pattern Recognition 65, 58-70, 2017	17	2017
Measuring dependency via intrinsic dimensionality S Romano, O Chelly, V Nguyen, J Bailey, ME Houle 2016 23rd International Conference on Pattern Recognition (ICPR), 1207-1212, 2016	14	2016
A framework to adjust dependency measure estimates for chance S Romano, NX Vinh, J Bailey, K Verspoor Proceedings of the 2016 SIAM international conference on data mining, 423-431, 2016	11	2016
Generalized information theoretic cluster validity indices for soft clusterings Y Lei, JC Bezdek, J Chan, NX Vinh, S Romano, J Bailey 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), 24-31, 2014	9	2014
Unbiased multivariate correlation analysis Y Wang, S Romano, V Nguyen, J Bailey, X Ma, ST Xia Thirty-First AAAI Conference on Artificial Intelligence, 2017	6	2017
The randomized information coefficient: assessing dependencies in noisy data S Romano, NX Vinh, K Verspoor, J Bailey Machine Learning 107 (3), 509-549, 2018	4	2018
Normalized Loss Functions for Deep Learning with Noisy Labels X Ma, H Huang, Y Wang, S Romano, S Erfani, J Bailey arXiv preprint arXiv:2006.13554, 2020	1	2020
Enhancing Diagnostics for Invasive Aspergillosis using Machine Learning S Romano, J Bailey, L Cavedon, O Morrissey, M Slavin, K Verspoor	1	2014
Design and adjustment of dependency measures S Romano		2015
Analisi di dati clinici relativi alla terapia per l'epatite C S Romano		2009
Sicurezza dei dati in sistemi di mobile health: metodologie ed esempi S Romano		2008
Data Security in Mobile Health Systems: Methodology and Examples S Romano Università degli Studi di Padova, 2008		2008
Hepatitis C Therapy: Clinical Data Analysis S Romano Università degli Studi di Padova, 0

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