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#p_feurer

SBF+25

Overtuning in Hyperparameter Optimization

AutoML 2025 - Methods Track

#p_bischl #p_feurer

ZSH+25

CAPO: Cost-Aware Prompt Optimization

AutoML 2025

#p_bischl #p_feurer

KFE25

In-Context Learning of Soft Nearest Neighbor Classifiers for Intelligible Tabular Machine Learning

TRL @ACL 2025

#p_feurer

BCD+25

OpenML: Insights From 10 Years and More Than a Thousand Papers

Patterns 6.7. Jul. 2025

#p_bischl #p_feurer

BGS+25

Carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks

Preprint (Jun. 2025)

#p_feurer

RSB+25

Efficiently Warmstarting MCMC for BNNs

FPI @ICLR 2025

#p_bischl #p_feurer #p_ruegamer

NSB+24

Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization

NeurIPS 2024

#p_bischl #p_feurer #p_nagler

KNF+24

Towards Localization via Data Embedding for TabPFN

TLR @NeurIPS 2024

#p_feurer #p_nagler

BFB+24

AMLTK: A Modular AutoML Toolkit in Python

The Journal of Open Source Software 9.100. Aug. 2024

#p_feurer

HLE+24

Position: Why We Must Rethink Empirical Research in Machine Learning

ICML 2024

#p_bischl #p_boulesteix #p_feurer #p_huellermeier #p_ruegamer

LKK+24

Position: A Call to Action for a Human-Centered AutoML Paradigm

ICML 2024

#p_bischl #p_feurer

RKC+24

Interpretable Machine Learning for TabPFN

XAI 2024

#p_bischl #p_feurer #p_nagler #p_ruegamer

KFB+24

Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning

DMLR @ICLR 2024

#p_bischl #p_feurer

WPF+24

Can Fairness Be Automated? Guidelines and Opportunities for Fairness-Aware AutoML

Journal of Artificial Intelligence Research 79. Feb. 2024

#p_bischl #p_feurer

FHF+23

OpenML-CTR23 - A Curated Tabular Regression Benchmarking Suite

AutoML 2023 - Workshop Track

#p_bischl #p_feurer

FEB+23

Mind the Gap: Measuring Generalization Performance Across Multiple Objectives

IDA 2023

#p_bischl #p_feurer

BCF+21

OpenML Benchmarking Suites

Track on Datasets and Benchmarks @NeurIPS 2021

#p_bischl #p_feurer
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