Simone Romano

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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 Computing Technologies, RMIT UniversityVerified email at rmit.edu.au
Karin VerspoorExecutive Dean, School of Computing Technologies, RMIT UniversityVerified email at rmit.edu.au
James C. BezdekUniversity of Melbourne, Computer and Information SystemsVerified email at unimelb.edu.au
Yisen WangAssistant Professor, Peking UniversityVerified email at pku.edu.cn
Xingjun MaAssociate Professor, School of Computer Science, Fudan UniversityVerified email at unimelb.edu.au
Sarah M. ErfaniSenior Lecturer and DECRA Fellow, Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Hanxun HuangThe University of MelbourneVerified email at student.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
Michael E. HoulePrincipal Fellow, School of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Oussama ChellyMicrosoft AI & IoT Insider Lab EuropeVerified email at microsoft.com
Shu-Tao XiaTsinghua UniversityVerified email at sz.tsinghua.edu.cn
Lawrence CavedonSchool of Computing Technologies, 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

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Verified email at simoneromano.com - Homepage

Machine Learning Artificial Intelligence Deep learning Data Mining


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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	125	2016
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	115	2014
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	111	2020
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	97	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	64	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	36	2017
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	30	2016
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	22	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	14	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	14	2014
Unbiased multivariate correlation analysis Y Wang, S Romano, V Nguyen, J Bailey, X Ma, ST Xia Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	12	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	9	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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