Marius Lindauer
24 papers · 2017–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (8) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (7) π Cross-Pollinator (4)
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Cross-Pollinator
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Renaissance Researcher
(5)
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Taxonomy Completionist
(33)
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Grand Slam
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Dynamic Duo
(14)
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Deep Specialist
(15)
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Keyword Collector
(71)
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Century Club
(23)
π₯
Unstoppable
(9)
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Prolific Year
(6)
Conferences
AUTOML (6)
ICML (4)
IJCAI (4)
JMLR (4)
NIPS (3)
AAAI (2)
ICLR (1)
Top co-authors
Keywords
hyperparameter optimization
(14)
bayesian optimization
(6)
surrogate model
(3)
reinforcement learning
(2)
neural architecture search
(2)
sample efficiency
(2)
automated machine learning
(2)
algorithm selection
(2)
deep reinforcement learning
(2)
algorithm configuration
(2)
game theory
(1)
policy learning
(1)
model architecture
(1)
deep learning
(1)
black-box optimization
(1)
interpretable machine learning
(1)
expected improvement
(1)
preference learning
(1)
value iteration
(1)
game playing
(1)
Papers
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
AAAI 2026
DeepCAVE: A Visualization and Analysis Tool for Automated Machine Learning
JMLR 2025
Revisiting Learning Rate Control
AUTOML 2025
Auto-nnU-Net: Towards Automated Medical Image Segmentation
AUTOML 2025
Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning
AAAI 2024
Position: A Call to Action for a Human-Centered AutoML Paradigm
ICML 2024
Learning Activation Functions for Sparse Neural Networks
AUTOML 2023
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
AUTOML 2023
AutoRL Hyperparameter Landscapes
AUTOML 2023
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
NIPS 2023
Symbolic Explanations for Hyperparameter Optimization
AUTOML 2023
Hyperparameters in Reinforcement Learning and How To Tune Them
ICML 2023
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning
JMLR 2022
$\pi$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization
ICLR 2022
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
JMLR 2022
Self-Paced Context Evaluation for Contextual Reinforcement Learning
ICML 2021
Well-tuned Simple Nets Excel on Tabular Datasets
NIPS 2021
TempoRL: Learning When to Act
ICML 2021
Explaining Hyperparameter Optimization via Partial Dependence Plots
NIPS 2021
DACBench: A Benchmark Library for Dynamic Algorithm Configuration
IJCAI 2021
Best Practices for Scientific Research on Neural Architecture Search
JMLR 2020
An Evolution Strategy with Progressive Episode Lengths for Playing Games
IJCAI 2019
Neural Networks for Predicting Algorithm Runtime Distributions
IJCAI 2018
AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract)
IJCAI 2017