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02/01/2023
Approximating the Shapley Value without Marginal Contributions
The Shapley value is arguably the most popular approach for assigning a ...
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02/01/2023
Iterative Deepening Hyperband
Hyperparameter optimization (HPO) is concerned with the automated search...
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01/30/2023
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification
It is well known that accurate probabilistic predictors can be trained t...
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12/01/2022
AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration
We study the algorithm configuration (AC) problem, in which one seeks to...
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05/20/2022
On Calibration of Ensemble-Based Credal Predictors
In recent years, several classification methods that intend to quantify ...
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03/11/2022
On the Difficulty of Epistemic Uncertainty Quantification in Machine Learning: The Case of Direct Uncertainty Estimation through Loss Minimisation
Uncertainty quantification has received increasing attention in machine ...
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02/09/2022
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget
We consider the combinatorial bandits problem with semi-bandit feedback ...
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02/03/2022
A Survey of Methods for Automated Algorithm Configuration
Algorithm configuration (AC) is concerned with the automated search of t...
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02/02/2022
Non-Stationary Dueling Bandits
We study the non-stationary dueling bandits problem with K arms, where t...
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09/13/2021
Machine Learning for Online Algorithm Selection under Censored Feedback
In online algorithm selection (OAS), instances of an algorithmic problem...
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11/02/2020
Multi-Armed Bandits with Censored Consumption of Resources
We consider a resource-aware variant of the classical multi-armed bandit...
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02/11/2020
Online Preselection with Context Information under the Plackett-Luce Model
We consider an extension of the contextual multi-armed bandit problem, i...
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07/13/2019
Preselection Bandits under the Plackett-Luce Model
In this paper, we introduce the Preselection Bandit problem, in which th...
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03/23/2019