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Multivariate normal approximation of the maximum likelihood estimator via the delta method. Anastasiou, A. & Gaunt, R. E. (2020). Brazilian Journal of Probability and Statistics 34, 136-149.
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Detecting multiple generalized change-points by isolating single ones. Anastasiou, A. & Fryzlewicz, P. (2020+). With supplement. arXiv:1901.10852 [stat.ME]. In submission.
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Wasserstein distance error bounds for the multivariate normal approximation of the maximum likelihood estimator. Anastasiou, A. & Gaunt, R. E. (2020+) arXiv:2005.05208 [math.ST]. In submission.
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Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT. Anastasiou, A, & Balasubramanian, K. & Erdogdu, M. (2019). Proceedings of the Conference on Learning Theory (COLT) 2019.
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Assessing the multivariate normal approximation of the maximum likelihood estimator from high-dimensional, heterogeneous data. Anastasiou, A. (2018). Electronic Journal of Statistics, 12, No. 2, 3794-3828.
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Bounds for the normal approximation of the maximum likelihood estimator. Anastasiou, A. & Reinert, G. (2017). Bernoulli 23, 191-218.
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Bounds for the asymptotic normality of the maximum likelihood estimator using the Delta method. Anastasiou, A. & Ley, C. (2017). ALEA, Lat. Am. J. Probab. Math. Stat. 14, 153-171.
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Bounds for the normal approximation of the maximum likelihood estimator from m-dependent random variables. Anastasiou, A. (2017). Statistics & Probability Letters 129, 171-181.