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Publications

Dommel, P., & Pichler, A. (2023). (in press). Uniform Function Estimators in Reproducing Kernel Hilbert Spaces. Pure and Applied Functional Analysis.
Dommel, P., & Pichler, A. (2023). Dynamic Programming For Data Independent Decision Sets. Journal of Convex Analysis, 30(3). https://www.heldermann.de/JCA/JCA30/JCA303/jca30042.htm
Kretzschmar, F., Uhlig, D., Pichler, A., Kanoun, O., & Barioul, R. (2023). (in press). Nadaraya-Watson Time Series Early Classification for Gesture Recognition. In B. Meyer, U. Thomas, … O. Kanoun (Eds.), Hybrid Societies - Humans Interacting with Embodied Technologies.
Lakshmanan, R., & Pichler, A. (2023). (in press). Expectiles In Risk Averse Stochastic Programming and Dynamic Optimization. Pure and Applied Functional Analysis.
Lakshmanan, R., Pichler, A., & Potts, D. (2023). Nonequispaced Fast Fourier Transform Boost for the Sinkhorn Algorithm. ETNA - Electronic Transactions on Numerical Analysis, 58, 289–315. https://doi.org/10.1553/etna_vol58s289
Rehm, M., Sanseverino, G., Caporaso, T., Lanzotti, A., Odenwald, S., & Pichler, A. (2023). (in press). A Parametric Model to Assess Minnesota Dexterity Test with IMU. In B. Meyer, U. Thomas, … O. Kanoun (Eds.), Hybrid Societies - Humans Interacting with Embodied Technologies.
Shapiro, A., & Pichler, A. (2023). Conditional Distributionally Robust Functionals. Operations Research. https://doi.org/10.1287/opre.2023.2470
Ernst, O., Pichler, A., & Sprungk, B. (2022). Wasserstein Sensitivity of Risk and Uncertainty Propagation. SIAM Journal on Uncertainty Quantification, 10(3). https://doi.org/10.1137/20M1325459
Kretzschmar, F., Pichler, A., & Beggiato, M. (2022). Detection of Discomfort in Autonomous Driving via Stochastic Approximation. Advances in Transportation, 60, 87–92. https://doi.org/10.54941/ahfe1002437
Pichler, A., & Schlotter, R. (2022). Risk-Averse Optimal Control in Continuous Time by Nesting Risk Measures. Mathematics of Operation Research. https://doi.org/10.1287/moor.2022.1314
Dommel, P., & Pichler, A. (2021). Convex Risk Measures based on Divergence. Pure and Applied Functional Analysis, 6(6). http://yokohamapublishers.jp/online2/oppafa/vol6/p1157.html
Dommel, P., Pichler, A., & Beggiato, M. (2021). Comparison of a Logistic and SVM Model to Detect Discomfort in Automated Driving. In D. Russo, T. Ahram, W. Karwowski, G. Di Bucchianico, … R. Taiar (Eds.), Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing. https://doi.org/10.1007/978-3-030-68017-6_7
Pichler, A., & Shapiro, A. (2021). Mathematical Foundations of Distributionally Robust Multistage Optimization. SIAM Journal on Optimization, 31(4). https://doi.org/10.1137/21M1390517
Pichler, A., & Weinhardt, M. (2021). The nested Sinkhorn divergence to learn the nested distance. Computational Management Science, 19(2). https://doi.org/10.1007/s10287-021-00415-7