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Mixture of experts distributional regression: implementation using robust estimation with adaptive first-order methods

Advances in statistical analysis : AStA : a journal of the German Statistical Society, 2024-06, Vol.108 (2), p.351-373

2024

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deepregression : A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression

Journal of statistical software, 2023, Vol.105 (2), p.1-31

2023

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Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features

Computational statistics, 2022-11, Vol.37 (5), p.2671-2692

2022

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A geometric framework for outlier detection in high‐dimensional data

Wiley interdisciplinary reviews. Data mining and knowledge discovery, 2023-05, Vol.13 (3), p.e1491-n/a

2023

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Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers

IEEE transactions on evolutionary computation, 2022-12, Vol.26 (6), p.1-1

2022

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Fairness Audits and Debiasing Using \pkg{mlr3fairness}

The R journal, 2023-08, Vol.15 (1), p.234-253

2023

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Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML

The Journal of artificial intelligence research, 2024-02, Vol.79, p.639-677

2024

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Strategies to optimise machine learning classification performance when using biomechanical features

Journal of biomechanics, 2024-03, Vol.165, p.111998-111998, Article 111998

2024

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Real-World Demonstration of AI to Clinical Cytometry for Rapid and Reliable Decision Support and Automated Reporting of Blood Cancers Including B-NHL and Acute Leukemias

Blood, 2023-11, Vol.142 (Supplement 1), p.3661-3661

2023

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Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview

ACM transactions on evolutionary learning, 2023-12, Vol.3 (4), p.1-50, Article 16

2023

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Kosten als Instrument zur Effizienzbeurteilung intensivmedizinischer Funktionseinheiten

Wiener klinisches Magazin : Beilage zur Wiener klinischen Wochenschrift, 2019-04, Vol.22 (2), p.86-93

2019

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mcboost: Multi-Calibration Boosting for R

Journal of open source software, 2021-08, Vol.6 (64), p.3453

2021

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Mind the Gap: Measuring Generalization Performance Across Multiple Objectives

Advances in Intelligent Data Analysis XXI, 2023, Vol.13876, p.130-142

2023

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Algorithmic Fairness

Applied Machine Learning Using mlr3 in R, 2024, Vol.1, p.316-324

1, 2024

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mlr3: A modern object-oriented machine learning framework in R

Journal of open source software, 2019-12, Vol.4 (44), p.1903

2019

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One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024, p.1305-1320

2024

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High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions

Intelligent Systems and Applications, 2019, Vol.1037, p.629-647

2019

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Sequential Pipelines

Applied Machine Learning Using mlr3 in R, 2024, Vol.1, p.163-173

1, 2024

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Multi-objective counterfactual fairness

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, p.328-331

2022

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A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, p.2136-2142

2022

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Learning multiple defaults for machine learning algorithms

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021, p.241-242

2021

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Meta-learning for symbolic hyperparameter defaults

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021, p.151-152

2021

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Non-sequential Pipelines and Tuning

Applied Machine Learning Using mlr3 in R, 2024, Vol.1, p.174-195

1, 2024

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Debiasing Classifiers: Is Reality at Variance With Expectation?

SSRN Electronic Journal

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Operability and chemotherapy responsiveness in advanced low-grade serous ovarian cancer. An analysis of the AGO Study Group metadatabase

Gynecologic oncology, 2016-03, Vol.140 (3), p.457-462

2016

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Mixture of experts distributional regression: implementation using robust estimation with adaptive first-order methods

deepregression : A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression

Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features

A geometric framework for outlier detection in high‐dimensional data

Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers

Fairness Audits and Debiasing Using \pkg{mlr3fairness}

Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML

Strategies to optimise machine learning classification performance when using biomechanical features

Real-World Demonstration of AI to Clinical Cytometry for Rapid and Reliable Decision Support and Automated Reporting of Blood Cancers Including B-NHL and Acute Leukemias

Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview

Kosten als Instrument zur Effizienzbeurteilung intensivmedizinischer Funktionseinheiten

mcboost: Multi-Calibration Boosting for R

Mind the Gap: Measuring Generalization Performance Across Multiple Objectives

Algorithmic Fairness

mlr3: A modern object-oriented machine learning framework in R

One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions

High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions

Sequential Pipelines

Multi-objective counterfactual fairness

A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models

Learning multiple defaults for machine learning algorithms

Meta-learning for symbolic hyperparameter defaults

Non-sequential Pipelines and Tuning

Debiasing Classifiers: Is Reality at Variance With Expectation?

Operability and chemotherapy responsiveness in advanced low-grade serous ovarian cancer. An analysis of the AGO Study Group metadatabase

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