1. K. Audhkhasi, A.M. Zavou, P.G. Georgiou, S.S. Narayanan, Theoretical analysis of diversity in an ensemble of automatic speech recognition systems. IEEE Trans. ASLP 22(3), 711–726 (2014)
2. P. Biuhlmann, Bagging, subagging and bragging for improving some prediction algorithms, in Recent Advances and Trends in Nonparametric Statistics, ed. by E.G. Akritas, D.N. Politis (Elsevier, Amsterdam, 2003)
3. J.K. Bradley, R.E. Schapire, FileterBoost: regression and classification on large datasets, in Advances in Neural Information Processing Systems, ed. by J.C. Platt et al., vol. 20 (MIT Press, Cambridge, 2008)
4. L. Breiman, Bagging predictors. Mach. Learn. 24(2), 123–140 (1996)
5. L. Breiman, Random forests. Mach. Learn. 45, 5–32 (2001)