Simone Romano

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	All	Since 2015
Citations	347	345
h-index	9	9
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20142015201620172018201920201 18 40 47 73 74 93

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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 WangAssistant Professor, School of EECS, Peking UniversityVerified email at pku.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
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
Lawrence CavedonComputer Science and IT, RMIT UniversityVerified email at rmit.edu.au
Orla MorrisseyAlfred Health and Monash UniversityVerified email at monash.edu
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


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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	90	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	60	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	56	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	38	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	25	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	20	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	16	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	12	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	11	2014
Unbiased Multivariate Correlation Analysis. Y Wang, S Romano, V Nguyen, J Bailey, X Ma, ST Xia AAAI, 2754-2760, 2017	7	2017
Normalized loss functions for deep learning with noisy labels X Ma, H Huang, Y Wang, S Romano, S Erfani, J Bailey International Conference on Machine Learning, 2020	6	2020
The randomized information coefficient: assessing dependencies in noisy data S Romano, NX Vinh, K Verspoor, J Bailey Machine Learning 107 (3), 509-549, 2018	5	2018
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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