Items where Schools and Departments is "Faculty of Actuarial Science & Insurance" and Year is 2026
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Abootalebi, Z., Tsanakas, A. 
ORCID: 0000-0003-4552-5532 & Zhu, R. ORCID: 0000-0002-9944-0369 (2026).
Differential Measurement of Proxy Discrimination.
.
Asimit, V. ORCID: 0000-0002-7706-0066, Chen, Z. ORCID: 0009-0009-6376-3850, Ichim, B. & Millossovich, P. ORCID: 0000-0001-8269-7507 (2026).
Parity Regression Estimation.
Risks, 14(4),
article number 94.
doi: 10.3390/risks14040094
Baxter-Moore, N. & Grant, P. ORCID: 0000-0002-2808-6219 (2026).
Introduction.
In: Baxter-Moore, N. & Grant, P. ORCID: 0000-0002-2808-6219 (Eds.),
Rock for Change: Interdisciplinary Perspectives on the Benefit Concert.
. Bloomsbury Publishing.
Belinga, R., Gond, J. ORCID: 0000-0002-9331-6957, Revelli, C. & Lagoarde‐Ségot, T. (2026).
The Dynamics of Theory and Value Performativity at Business Schools: Performative Valorization Work for Finance Education.
British Journal of Management,
article number e70038.
doi: 10.1111/1467-8551.70038
Chen, Z. ORCID: 0009-0009-6376-3850 & Millossovich, P. ORCID: 0000-0001-8269-7507 (2026).
Excess Verdicts Insurance.
North American Actuarial Journal,
pp. 1-22.
doi: 10.1080/10920277.2025.2596774
Dong, J., Zhu, R. ORCID: 0000-0002-9944-0369, Shang, X. & Xue, J-H. (2026).
Dawid-Skene-model-based label-noise mitigation for federated learning.
Information Sciences, 745,
article number 123425.
doi: 10.1016/j.ins.2026.123425
Dong, J., Zhu, R. ORCID: 0000-0002-9944-0369, Shang, X. & Xue, J-H. (2026).
Federated learning with noisy labels: A comprehensive and concise review of current methodologies and future directions.
Neural Networks, 201,
article number 108889.
doi: 10.1016/j.neunet.2026.108889
Lindholm, M., Richman, R., Tsanakas, A. ORCID: 0000-0003-4552-5532 & Wüthrich, M. V. (2026).
Sensitivity-based measures of discrimination in insurance pricing.
European Journal of Operational Research, 333(2),
pp. 601-615.
doi: 10.1016/j.ejor.2026.01.021
Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2026).
Bivariate Copula-Based Regression for Joint Modeling of Healthcare Visits.
Health Economics, 35(2),
pp. 332-345.
doi: 10.1002/hec.70059
Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2026).
Joint Modeling of Birth Outcomes Using a Copula Distributional Regression Approach.
Health Economics, 35(3),
pp. 399-408.
doi: 10.1002/hec.70067
Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2026).
Modeling Physician Visit Frequency and Costs Using a Copula Additive Distributional Regression Approach.
The Journal of the Royal Statistical Society, Series C (Applied Statistics), 75(2),
pp. 431-447.
doi: 10.1093/jrsssc/qlaf050
Wang, X., Zhu, R. ORCID: 0000-0002-9944-0369 & Xue, J-H. (2026).
UC-PUAL: A universally consistent classifier of positive-unlabelled data.
Pattern Recognition, 169,
article number 111892.
doi: 10.1016/j.patcog.2025.111892
Zheng, H., Wang, H., Zhu, R. ORCID: 0000-0002-9944-0369 & Xue, J-H. (2026).
A brief review of deep learning methods in mortality forecasting.
Annals of Actuarial Science, 20(1),
pp. 150-165.
doi: 10.1017/s1748499525100110