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Found 6 papers, 1 papers with code
Representation of Distribution Grid Expansion Costs in Power System Planning
With the method presented in this paper, a Feasible Planning Region (FPR) is developed, which represents the operational boundaries of the distribution grids for several expansion stages and thus represents an admissible solution space for the planning of distribution grids in systemic planning approaches.
Insights From Insurance for Fair Machine Learning
Tracing the interaction of uncertainty, fairness and responsibility in insurance provides a fresh perspective on fairness in machine learning.
Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity
As a concrete example, we focus on divergence risk measures based on f-divergence ambiguity sets, which are a widespread tool used to foster distributional robustness of machine learning systems.
Risk Measures and Upper Probabilities: Coherence and Stratification
Machine learning typically presupposes classical probability theory which implies that aggregation is built upon expectation.
Teleconnection patterns of different El Niño types revealed by climate network curvature
The diversity of El Ni\~no events is commonly described by two distinct flavors, the Eastern Pacific (EP) and Central Pacific (CP) types.
Bayesian Quadrature on Riemannian Data Manifolds
Riemannian manifolds provide a principled way to model nonlinear geometric structure inherent in data.
