Rabanus Derr
YOU?
Author Swipe
View article: Property Elicitation on Imprecise Probabilities
Property Elicitation on Imprecise Probabilities Open
Property elicitation studies which attributes of a probability distribution can be determined by minimizing a risk. We investigate a generalization of property elicitation to imprecise probabilities (IP). This investigation is motivated by…
View article: Three Types of Calibration with Properties and their Semantic and Formal Relationships
Three Types of Calibration with Properties and their Semantic and Formal Relationships Open
Fueled by discussions around "trustworthiness" and algorithmic fairness, calibration of predictive systems has regained scholars attention. The vanilla definition and understanding of calibration is, simply put, on all days on which the ra…
View article: Fairness and Randomness in Machine Learning: Statistical Independence and Relativization
Fairness and Randomness in Machine Learning: Statistical Independence and Relativization Open
Fair Machine Learning endeavors to prevent unfairness arising in the context of machine learning applications embedded in society. To this end, several mathematical fairness notions have been proposed. The most known and used notions turn …
View article: The Value of Ambiguous Commitments in Multi-Follower Games
The Value of Ambiguous Commitments in Multi-Follower Games Open
We study games in which a leader makes a single commitment, and then multiple followers (each with a different utility function) respond. In particular, we study ambiguous commitment strategies in these games, in which the leader may commi…
View article: An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm
An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm Open
Supervised learning has gone beyond the expected risk minimization framework. Central to most of these developments is the introduction of more general aggregation functions for losses incurred by the learner. In this paper, we turn toward…
View article: Forecast Evaluation and the Relationship of Regret and Calibration
Forecast Evaluation and the Relationship of Regret and Calibration Open
Machine learning is about forecasting. When the forecasts come with an evaluation metric the forecasts become useful. What are reasonable evaluation metrics? How do existing evaluation metrics relate? In this work, we provide a general str…
View article: Systems of Precision: Coherent Probabilities on Pre-Dynkin Systems and Coherent Previsions on Linear Subspaces
Systems of Precision: Coherent Probabilities on Pre-Dynkin Systems and Coherent Previsions on Linear Subspaces Open
In the literature on imprecise probability, little attention is paid to the fact that imprecise probabilities are precise on a set of events. We call these sets systems of precision. We show that, under mild assumptions, the system of prec…
View article: Strictly Frequentist Imprecise Probability
Strictly Frequentist Imprecise Probability Open
Strict frequentism defines probability as the limiting relative frequency in an infinite sequence. What if the limit does not exist? We present a broader theory, which is applicable also to random phenomena that exhibit diverging relative …
View article: Systems of Precision: Coherent Probabilities on Pre-Dynkin-Systems and Coherent Previsions on Linear Subspaces
Systems of Precision: Coherent Probabilities on Pre-Dynkin-Systems and Coherent Previsions on Linear Subspaces Open
In literature on imprecise probability little attention is paid to the fact that imprecise probabilities are precise on a set of events. We call these sets systems of precision. We show that, under mild assumptions, the system of precision…
View article: Fairness and Randomness in Machine Learning: Statistical Independence and Relativization
Fairness and Randomness in Machine Learning: Statistical Independence and Relativization Open
Fair Machine Learning endeavors to prevent unfairness arising in the context of machine learning applications embedded in society. Despite the variety of definitions of fairness and proposed "fair algorithms", there remain unresolved conce…