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Frank Hutter

CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning


Oct 11, 2021
Carolin Benjamins, Theresa Eimer, Frederik Schubert, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer

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SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization


Sep 20, 2021
Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, René Sass, Frank Hutter

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HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO


Sep 14, 2021
Katharina Eggensperger, Philipp Müller, Neeratyoy Mallik, Matthias Feurer, René Sass, Aaron Klein, Noor Awad, Marius Lindauer, Frank Hutter

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Multi-headed Neural Ensemble Search


Jul 09, 2021
Ashwin Raaghav Narayanan, Arber Zela, Tonmoy Saikia, Thomas Brox, Frank Hutter

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* 8 pages, 12 figures, 3 tables 
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Bag of Tricks for Neural Architecture Search


Jul 08, 2021
Thomas Elsken, Benedikt Staffler, Arber Zela, Jan Hendrik Metzen, Frank Hutter


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Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data


Jun 21, 2021
Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka

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TempoRL: Learning When to Act


Jun 09, 2021
André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer

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* Accepted at ICML'21 
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Self-Paced Context Evaluation for Contextual Reinforcement Learning


Jun 09, 2021
Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer

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DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization


May 20, 2021
Noor Awad, Neeratyoy Mallik, Frank Hutter

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DACBench: A Benchmark Library for Dynamic Algorithm Configuration


May 18, 2021
Theresa Eimer, André Biedenkapp, Maximilian Reimer, Steven Adriaensen, Frank Hutter, Marius Lindauer

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* Accepted at IJCAI 2021 
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Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization


May 03, 2021
Julia Guerrero-Viu, Sven Hauns, Sergio Izquierdo, Guilherme Miotto, Simon Schrodi, Andre Biedenkapp, Thomas Elsken, Difan Deng, Marius Lindauer, Frank Hutter

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How Powerful are Performance Predictors in Neural Architecture Search?


Apr 02, 2021
Colin White, Arber Zela, Binxin Ru, Yang Liu, Frank Hutter

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TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation


Mar 18, 2021
Samuel G. Müller, Frank Hutter

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On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning


Feb 26, 2021
Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra

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* 19 pages, accepted by AISTATS 2021 
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Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies


Feb 08, 2021
Fabio Ferreira, Thomas Nierhoff, Frank Hutter

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* AAAI 2021 Meta-Learning Workshop 
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In-Loop Meta-Learning with Gradient-Alignment Reward


Feb 05, 2021
Samuel Müller, André Biedenkapp, Frank Hutter

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* Accepted to Meta Learning Workshop at AAAI 
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Squirrel: A Switching Hyperparameter Optimizer


Dec 16, 2020
Noor Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, Andre' Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter


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Differential Evolution for Neural Architecture Search


Dec 11, 2020
Noor Awad, Neeratyoy Mallik, Frank Hutter

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Convergence Analysis of Homotopy-SGD for non-convex optimization


Nov 20, 2020
Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter

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* 21 pages, 14 figures, technical report 
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Hyperparameter Transfer Across Developer Adjustments


Oct 25, 2020
Danny Stoll, Jörg K. H. Franke, Diane Wagner, Simon Selg, Frank Hutter

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On the Importance of Domain Model Configuration for Automated Planning Engines


Oct 15, 2020
Mauro Vallati, Lukas Chrpa, Thomas L. McCluskey, Frank Hutter

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* Under consideration in Journal of Automated Reasoning 
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Smooth Variational Graph Embeddings for Efficient Neural Architecture Search


Oct 09, 2020
Jovita Lukasik, David Friede, Arber Zela, Heiner Stuckenschmidt, Frank Hutter, Margret Keuper

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* 13 pages, 4 figures, 6 tables 
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Sample-Efficient Automated Deep Reinforcement Learning


Oct 05, 2020
Jörg K. H. Franke, Gregor Köhler, André Biedenkapp, Frank Hutter

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Neural Model-based Optimization with Right-Censored Observations


Sep 29, 2020
Katharina Eggensperger, Kai Haase, Philipp Müller, Marius Lindauer, Frank Hutter

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NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search


Aug 22, 2020
Julien Siems, Lucas Zimmer, Arber Zela, Jovita Lukasik, Margret Keuper, Frank Hutter

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Auto-Sklearn 2.0: The Next Generation


Jul 08, 2020
Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter

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Prior-guided Bayesian Optimization


Jun 25, 2020
Artur Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter

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Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL


Jun 24, 2020
Lucas Zimmer, Marius Lindauer, Frank Hutter

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