Search results
Results: 108
Number of items: 108
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Magra, A., Baarslag, T., & Spreij, P. (2023). Querying User Preferences in Automated Negotiation. In R. Hadfi, W. Li, & T. Ito (Eds.), 2023 IEEE International Conference on Agents : ICA 2023 : 4-6 December 2023, Kyoto, Japan : proceedings (pp. 71-76). IEEE Computer Society. https://doi.org/10.1109/ICA58824.2023.00021
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Michielon, M., Khedher, A., & Spreij, P. (2023). On Wasserstein distances, barycenters, and the cross-section methodology for proxy credit curves. International Journal of Financial Engineering, 10( 2), Article 2250037. https://doi.org/10.1142/S2424786322500372
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Finesso, L., & Spreij, P. (2023). The Inverse Problem of Positive Autoconvolution. IEEE Transactions on Information Theory, 69(6), 4081-4092. https://doi.org/10.1109/TIT.2023.3244407 -
Gugushvili, S., van der Meulen, F., Schauer, M., & Spreij, P. (2023). Nonparametric Bayesian volatility learning under microstructure noise. Japanese Journal of Statistics and Data Science, 6(1), 551-571. https://doi.org/10.1007/s42081-022-00185-9 -
Belomestny, D., Gugushvili, S., Schauer, M., & Spreij, P. (2023). Weak solutions to gamma-driven stochastic differential equations. Indagationes Mathematicae, 34(4), 820-829. https://doi.org/10.1016/j.indag.2023.03.004 -
Delsing, G. A., Mandjes, M. R. H., Spreij, P. J. C., & Winands, E. M. M. (2022). On capital allocation for a risk measure derived from ruin theory. Insurance: Mathematics and Economics, 104, 76-98. https://doi.org/10.1016/j.insmatheco.2022.02.001 -
Belomestny, D., Gugushvili, S., Schauer, M., & Spreij, P. (2022). Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations. Bernoulli, 28(4), 2151-2180. https://doi.org/10.3150/21-BEJ1413
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