Simone Romano
Simone Romano
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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
Adjusting for chance clustering comparison measures
S Romano, NX Vinh, J Bailey, K Verspoor
Journal of Machine Learning Research 17 (134), 1-32, 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 Knowledgeá…, 2014
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
Discovering outlying aspects in large datasets
NX Vinh, J Chan, S Romano, J Bailey, C Leckie, K Ramamohanarao, ...
Data mining and knowledge discovery 30, 1520-1555, 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
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
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
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
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
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
The randomized information coefficient: Assessing dependencies in noisy data
S Romano, NX Vinh, K Verspoor, J Bailey
Machine Learning 107, 509-549, 2018
Enhancing Diagnostics for Invasive Aspergillosis using Machine Learning
S Romano, J Bailey, L Cavedon, O Morrissey, M Slavin, K Verspoor
Design and Adjustment of Dependency Measures
S Romano
University of Melbourne, Department of Computing and Information Systems, 2015
Analisi di dati clinici relativi alla terapia per l'epatite C
S Romano
Sicurezza dei dati in sistemi di mobile health: metodologie ed esempi
S Romano
Data Security in Mobile Health Systems: Methodology and Examples
S Romano
UniversitÓ degli Studi di Padova, 2008
Hepatitis C Therapy: Clinical Data Analysis
S Romano
UniversitÓ degli Studi di Padova, 0
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