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Robert C. Williamson

Scoring Rules and Calibration for Imprecise Probabilities

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Oct 30, 2024
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Causal modelling without counterfactuals and individualised effects

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Jul 24, 2024
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Five reasons against assuming a data-generating distribution in Machine Learning

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Jul 24, 2024
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An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm

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Jun 04, 2024
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Geometry and Stability of Supervised Learning Problems

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Mar 04, 2024
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Four Facets of Forecast Felicity: Calibration, Predictiveness, Randomness and Regret

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Jan 25, 2024
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A General Framework for Learning under Corruption: Label Noise, Attribute Noise, and Beyond

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Jul 17, 2023
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Insights From Insurance for Fair Machine Learning: Responsibility, Performativity and Aggregates

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Jun 26, 2023
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The Geometry of Mixability

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Feb 23, 2023
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Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity

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Aug 05, 2022
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