116110
Lehrstuhl für Stochastik und Institut für Statistik und Wirtschaftsmathematik Also known as:Lehrstuhl für Stochastik und Institut für Statistik u. Wirtschaftsmathematik| ID | I:(DE-82)116110_20140620 |
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Journal Article
Adaptive thresholds for monitoring and screening in imbalanced samples: optimality and boosting sensitivity
Annals of the Institute of Statistical Mathematics (2026) [10.1007/s10463-025-00970-9]
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Journal Article
Is There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?
Applied stochastic models in business and industry 41(2), e70004 (2025) [10.1002/asmb.70004]
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Journal Article
Discussion on Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models
Environmetrics: the official journal of the International Environmetrics Society (TIES) 36(2), e70003 (2025) [10.1002/env.70003]
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Journal Article
Detection of suspicious areas in non-stationary Gaussian fields and locally averaged non-Gaussian linear fields
Journal of statistical planning and inference : JSPI 238, 106273 (2025) [10.1016/j.jspi.2025.106273]
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Journal Article
Concentration and Model Selection Consistency of the Group Lasso for α-Mixing Errors
Stat : the ISI's Journal for the Rapid Dissemination of Statistics Research 14(1), e70035 (2025) [10.1002/sta4.70035]
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Journal Article
General adapted‐threshold monitoring in discrete environments and rules for imbalanced classes
Statistica Neerlandica 79(1), e12352 (2024) [10.1111/stan.12352]
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Journal Article
Projection inference for high-dimensional covariance matrices with structured shrinkage targets
Electronic journal of statistics : EJS 18(1), 1643-1676 (2024) [10.1214/24-EJS2225]
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Journal Article
Are minimum variance portfolios in multi-factor models long in low-beta assets?
Mathematics and financial economics 18, 151-170 (2024) [10.1007/s11579-024-00366-y]
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Contribution to a book/Contribution to a conference proceedings
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning
International Conference on Artificial Intelligence and Statistics, 2-4 May 2024, Palau de Congressos, Valencia, Spain / Editors: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
27. International Conference on Artificial Intelligence and Statistics, AISTATS 2024, ValenicaValenica, Spain, 2 May 2024 - 4 May 2024
MLResearchPress, Proceedings of machine learning research 238, 1333-1341 (2024)
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Journal Article (Review Article)
Flexible nonlinear inference and change-point testing of high-dimensional spectral density matrices
Journal of multivariate analysis : JMVA 199(January 2024), 105245 (2024) [10.1016/j.jmva.2023.105245]
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