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 | 428 | 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 | 219 | 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 | 151 | 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 | 147 | 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 | 91 | 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 | 63 | 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 | 42 | 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 | 31 | 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 | 26 | 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 | 19 | 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 |
The randomized information coefficient: Assessing dependencies in noisy data S Romano, NX Vinh, K Verspoor, J Bailey Machine Learning 107, 509-549, 2018 | 13 | 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 University of Melbourne, Department of Computing and Information Systems, 2015 | | 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 | | |