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Data-Driven Methods for Modelling and Optimizing the Empirical Performance of Deep Neural Networks

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Publications

Hyperparameter Transfer Across Developer Adjustments

Author(s): Danny Stoll, Jörg Franke, Diane Wagner, Simon Selg, Frank Hutter
Published in: NeurIPS MetaLearning Workshop, 2020

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift

Author(s): Zaidi, Sheheryar; Zela, Arber; Elsken, Thomas; Holmes, Chris; Hutter, Frank; Teh, Yee Whye
Published in: NeurIPS Workshop on Uncertainty in Deep Learning, Issue 6, 2020

Transferring Optimally Across Data Distributions via Homotopy Methods

Author(s): Matilde Gargiani, Andrea Zanelli, Quoc Tran Dinh, Moritz Diehl, Frank Hutter
Published in: ICLR 2020, 2020

Meta-Learning of Neural Architectures for Few-Shot Learning

Author(s): Thomas Elsken, Benedikt Staffler, Jan Hendrik Metzen, Frank Hutter
Published in: CVPR 2020, 2020

Sample-Efficient Automated Deep Reinforcement Learning

Author(s): Jörg Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
Published in: ICLR 2021, 2021

Understanding and Robustifying Differentiable Architecture Search

Author(s): Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, Frank Hutter
Published in: ICLR 2020, 2020

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

Author(s): Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra
Published in: AISTATS 2021, 2021

Combining Hyperband and Bayesian Optimization

Author(s): Stefan Falkner, Aaron Klein, Frank Hutter
Published in: Proceedings of BayesOpt 2017, 2017

Learning curve predictionwith bayesian neural networks

Author(s): Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter
Published in: proceedings of ICLR, 2017

RoBO: A Flexible and Robust Bayesian Optimization Framework in Python

Author(s): Aaron Klein, Stefan Falkner, Numair Mansur, Frank Hutter
Published in: Proceedings of BayesOpt 2017, 2017

The Sacred Infrastructure for Computational Research

Author(s): Klaus Greff, Aaron Klein, Martin Chovanec, Frank Hutter, Jürgen Schmidhuber
Published in: proceedings of the 15th python in science conference, 2017

An Empirical Study of Hyperparameter Importance Across Datasets

Author(s): Jan N. van Rijn, Frank Hutter
Published in: proceedings of AutoML, 2017

The reparameterization trick for acquisition functions

Author(s): James T. Wilson, Riccardo Moriconi, Frank Hutter, Marc Peter Deisenroth
Published in: Proceedings of BayesOpt 2017, 2017

BOHB: Robust and Efficient Hyperparameter Optimization at Scale

Author(s): Falkner, Stefan; Klein, Aaron; Hutter, Frank
Published in: ICML 2018, Issue 5, 2018

Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search

Author(s): Zela, Arber; Klein, Aaron; Falkner, Stefan; Hutter, Frank
Published in: AutoML Workshop, Issue 1, 2018

Maximizing acquisition functions for Bayesian optimization

Author(s): Wilson, James T.; Hutter, Frank; Deisenroth, Marc Peter
Published in: NeurIPS 2018, Issue 1, 2018

Hyperparameter Importance Across Datasets

Author(s): Jan N. van Rijn, Frank Hutter
Published in: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '18, 2018, Page(s) 2367-2376
DOI: 10.1145/3219819.3220058

Decoupled Weight Decay Regularization

Author(s): Loshchilov, Ilya; Hutter, Frank
Published in: ICLR 2019, Issue 5, 2019

Learning to Design RNA

Author(s): Runge, Frederic; Stoll, Danny; Falkner, Stefan; Hutter, Frank
Published in: ICLR 2019, Issue 5, 2019

Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari

Author(s): Chrabaszcz, Patryk; Loshchilov, Ilya; Hutter, Frank
Published in: IJCAI 2018, Issue 1, 2018

NAS-Bench-101: Towards Reproducible Neural Architecture Search

Author(s): Ying, Chris; Klein, Aaron; Real, Esteban; Christiansen, Eric; Murphy, Kevin; Hutter, Frank
Published in: ICML 2019, Issue 5, 2019

Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution - Published as a conference paper at ICLR 2019

Author(s): Hutter, Frank Elsken, Thomas Metzen, Jan Hendrik
Published in: 2019

Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings

Author(s): Matilde Gargiani, Aaron Klein, Stefan Falkner, Frank Hutter
Published in: 2019

Practical Automated Machine Learning for the AutoML Challenge 2018

Author(s): Matthias Feurer Katharina Eggensperger Stefan Falkner Marius Lindauer Frank Hutter
Published in: ICML 2018, 2018

Towards Further Automation in AutoML

Author(s): Matthias Feurer Frank Hutter
Published in: ICML 2018, 2018

Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control

Author(s): Jör Franke, Jörg Gregor Köhler Noor Awad Frank Hutter
Published in: NeurIPS 2019, 2019

NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search

Author(s): Arber Zela, Julien Siems, Frank Hutter
Published in: ICLR 2020, 2020

MDP Playground: A Design and Debug Testbed for Reinforcement Learning

Author(s): Rajan, Raghu; Diaz, Jessica Lizeth Borja; Guttikonda, Suresh; Ferreira, Fabio; Biedenkapp, André; von Hartz, Jan Ole; Hutter, Frank
Published in: arXiv preprint, Issue 17, 2021

On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs

Author(s): Matilde Gargiani, Andrea Zanelli, Moritz Diehl, Frank Hutter
Published in: 2020

OpenML Benchmarking Suites and the OpenML100

Author(s): Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G.; van Rijn, Jan N.; Vanschoren, Joaquin
Published in: Issue 1, 2017

A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets

Author(s): Chrabaszcz, Patryk; Loshchilov, Ilya; Hutter, Frank
Published in: arXiv, Issue 5, 2017

Neural Model-based Optimization with Right-Censored Observations

Author(s): Katharina Eggensperger, Kai Haase, Philipp Müller, Marius Lindauer, Frank Hutter
Published in: arXiv, 2020

Auto-sklearn 2.0: The Next Generation

Author(s): Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
Published in: arXiv, 2020

Neural Architecture Search: A Survey

Author(s): Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank
Published in: JMLR, Issue 5, 2019, ISSN 1533-7928

Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019

Author(s): Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Fabio Ferreira, Isabelle Guyon, Sirui Hong, Frank Hutter, Rongrong Ji, Julio C. S. Jacques Junior, Ge Li, Marius Lindauer, Zhipeng Luo, Meysam Madadi, Thomas Nierhoff, Kangning Niu, Chunguang Pan, Danny Stoll, Sebastien Treguer, Jin Wang, Peng Wang, Chenglin Wu, Youcheng Xiong, Arber Zela, Yang Zhang
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence, Issue 43/9, 2021, Page(s) 3108-3125, ISSN 0162-8828
DOI: 10.1109/tpami.2021.3075372

Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow

Author(s): Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox
Published in: Computer Vision – ECCV 2018 - 15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part VII, Issue 11211, 2018, Page(s) 677-693
DOI: 10.1007/978-3-030-01234-2_40

Automated Machine Learning: Methods, Systems, Challenges

Author(s): Hutter, Frank, Kotthoff, Lars, Vanschoren, Joaquin (Eds.)
Published in: The Springer Series on Challenges in Machine Learning, 2019

Fast Bayesian hyperparameteroptimization on large datasets

Author(s): Aaron Klein Stefan Falkner Simon Bartels Philipp Hennig Frank Hutter
Published in: Electronic Journal of Statistics, 2017, ISSN 1935-7524