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

Hyperparameter Transfer Across Developer Adjustments

Autores: Danny Stoll, Jörg Franke, Diane Wagner, Simon Selg, Frank Hutter
Publicado en: NeurIPS MetaLearning Workshop, 2020
Editor: online

Multi-headed Neural Ensemble Search

Autores: Ashwin Raaghav Narayanan, Arber Zela, Tonmoy Saikia, Thomas Brox, Frank Hutter
Publicado en: ICML 2021 Workshop on Uncertainty and Robustness in Deep Learning, 2021
Editor: online

Transferring Optimally Across Data Distributions via Homotopy Methods

Autores: Matilde Gargiani, Andrea Zanelli, Quoc Tran Dinh, Moritz Diehl, Frank Hutter
Publicado en: ICLR 2020, 2020
Editor: online

NAS-Bench-x11 and the Power of Learning Curves

Autores: Shen Yan, Colin White, Yash Savani, Frank Hutter
Publicado en: NeurIPS 2021, 2021
Editor: online

Meta-Learning of Neural Architectures for Few-Shot Learning

Autores: Thomas Elsken, Benedikt Staffler, Jan Hendrik Metzen, Frank Hutter
Publicado en: CVPR 2020, 2020
Editor: IEEE

OpenML Benchmarking Suites

Autores: Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Pieter Gijsbers, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan van Rijn, Joaquin Vanschoren
Publicado en: NeurIPS Datasets and Benchmarks 2021, 2021
Editor: online

Sample-Efficient Automated Deep Reinforcement Learning

Autores: Jörg Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
Publicado en: ICLR 2021, 2021
Editor: online

Understanding and Robustifying Differentiable Architecture Search

Autores: Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, Frank Hutter
Publicado en: ICLR 2020, 2020
Editor: online

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

Autores: Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra
Publicado en: AISTATS 2021, 2021
Editor: Proceedings of Machine Learning Research

Combining Hyperband and Bayesian Optimization

Autores: Stefan Falkner, Aaron Klein, Frank Hutter
Publicado en: Proceedings of BayesOpt 2017, 2017
Editor: published online

Learning curve predictionwith bayesian neural networks

Autores: Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter
Publicado en: proceedings of ICLR, 2017
Editor: published online

RoBO: A Flexible and Robust Bayesian Optimization Framework in Python

Autores: Aaron Klein, Stefan Falkner, Numair Mansur, Frank Hutter
Publicado en: Proceedings of BayesOpt 2017, 2017
Editor: published online

The Sacred Infrastructure for Computational Research

Autores: Klaus Greff, Aaron Klein, Martin Chovanec, Frank Hutter, Jürgen Schmidhuber
Publicado en: proceedings of the 15th python in science conference, 2017
Editor: published online

An Empirical Study of Hyperparameter Importance Across Datasets

Autores: Jan N. van Rijn, Frank Hutter
Publicado en: proceedings of AutoML, 2017
Editor: published online

The reparameterization trick for acquisition functions

Autores: James T. Wilson, Riccardo Moriconi, Frank Hutter, Marc Peter Deisenroth
Publicado en: Proceedings of BayesOpt 2017, 2017
Editor: published online

BOHB: Robust and Efficient Hyperparameter Optimization at Scale

Autores: Falkner, Stefan; Klein, Aaron; Hutter, Frank
Publicado en: ICML 2018, Edición 5, 2018
Editor: ICML

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

Autores: Zela, Arber; Klein, Aaron; Falkner, Stefan; Hutter, Frank
Publicado en: AutoML Workshop, Edición 1, 2018
Editor: AutoML

Maximizing acquisition functions for Bayesian optimization

Autores: Wilson, James T.; Hutter, Frank; Deisenroth, Marc Peter
Publicado en: NeurIPS 2018, Edición 1, 2018
Editor: NeurIPS

Hyperparameter Importance Across Datasets

Autores: Jan N. van Rijn, Frank Hutter
Publicado en: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '18, 2018, Página(s) 2367-2376, ISBN 9781-450355520
Editor: ACM Press
DOI: 10.1145/3219819.3220058

Decoupled Weight Decay Regularization

Autores: Loshchilov, Ilya; Hutter, Frank
Publicado en: ICLR 2019, Edición 5, 2019
Editor: ICLR

Learning to Design RNA

Autores: Runge, Frederic; Stoll, Danny; Falkner, Stefan; Hutter, Frank
Publicado en: ICLR 2019, Edición 5, 2019
Editor: ICLR

Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari

Autores: Chrabaszcz, Patryk; Loshchilov, Ilya; Hutter, Frank
Publicado en: IJCAI 2018, Edición 1, 2018
Editor: IJCAI

NAS-Bench-101: Towards Reproducible Neural Architecture Search

Autores: Ying, Chris; Klein, Aaron; Real, Esteban; Christiansen, Eric; Murphy, Kevin; Hutter, Frank
Publicado en: ICML 2019, Edición 5, 2019
Editor: ICML

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

Autores: Hutter, Frank Elsken, Thomas Metzen, Jan Hendrik
Publicado en: 2019
Editor: open review

Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings

Autores: Matilde Gargiani, Aaron Klein, Stefan Falkner, Frank Hutter
Publicado en: 2019
Editor: online

Practical Automated Machine Learning for the AutoML Challenge 2018

Autores: Matthias Feurer Katharina Eggensperger Stefan Falkner Marius Lindauer Frank Hutter
Publicado en: ICML 2018, 2018
Editor: Online

Towards Further Automation in AutoML

Autores: Matthias Feurer Frank Hutter
Publicado en: ICML 2018 workshop on AutoML, 2018
Editor: Online

Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control

Autores: Jör Franke, Jörg Gregor Köhler Noor Awad Frank Hutter
Publicado en: NeurIPS 2019, 2019
Editor: Online

Bag of Tricks for Neural Architecture Search

Autores: Thomas Elsken, Benedikt Staffler, Arber Zela, Jan Hendrik Metzen, Frank Hutter
Publicado en: CVPR 2021 Workshop on Neural Architecture Search, 2021
Editor: online

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

Autores: Katharina Eggensperger, Philipp Müller, Neeratyoy Mallik, Matthias Feurer, Rene Sass, Aaron Klein, Noor Awad, Marius Lindauer, Frank Hutter
Publicado en: NeurIPS Datasets and Benchmarks 2021, 2021
Editor: online

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

Autores: Samuel G. Müller, Frank Hutter
Publicado en: ICCV 2021, 2021
Editor: online

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

Autores: Arber Zela, Julien Siems, Frank Hutter
Publicado en: ICLR 2020, 2020
Editor: online

Bayesian Optimization with a Prior for the Optimum

Autores: Artur Souza, Luigi Nardi, Leonardo B. Oliveira,Kunle Olukotun, Marius Lindauer, Frank Hutte
Publicado en: ECML PKDD 2021, 2021
Editor: online

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift

Autores: Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C Holmes, Frank Hutter, Yee Teh
Publicado en: NeurIPS 2021, 2021
Editor: online

How Powerful are Performance Predictors in Neural Architecture Search?

Autores: Colin White, Arber Zela, Robin Ru, Yang Liu, Frank Hutter
Publicado en: NeurIPS 2021, 2021
Editor: online

Well-tuned Simple Nets Excel on Tabular Datasets

Autores: Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka
Publicado en: NeurIPS 2021, 2021
Editor: online

MDP Playground: A Design and Debug Testbed for Reinforcement Learning

Autores: Rajan, Raghu; Diaz, Jessica Lizeth Borja; Guttikonda, Suresh; Ferreira, Fabio; Biedenkapp, André; von Hartz, Jan Ole; Hutter, Frank
Publicado en: arXiv preprint, Edición 17, 2021
Editor: online

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

Autores: Matilde Gargiani, Andrea Zanelli, Moritz Diehl, Frank Hutter
Publicado en: 2020
Editor: online

OpenML Benchmarking Suites and the OpenML100

Autores: Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G.; van Rijn, Jan N.; Vanschoren, Joaquin
Publicado en: Edición 1, 2017
Editor: arXiv

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

Autores: Chrabaszcz, Patryk; Loshchilov, Ilya; Hutter, Frank
Publicado en: arXiv, Edición 5, 2017
Editor: arXiv

Neural Model-based Optimization with Right-Censored Observations

Autores: Katharina Eggensperger, Kai Haase, Philipp Müller, Marius Lindauer, Frank Hutter
Publicado en: arXiv, 2020
Editor: online

Auto-sklearn 2.0: The Next Generation

Autores: Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
Publicado en: arXiv, 2020
Editor: online

Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning

Autores: Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
Publicado en: arXiv, 2021
Editor: online

Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL

Autores: Lucas Zimmer, Marius Lindauer, Frank Hutter
Publicado en: IEEE Transactions on Pattern Analysis and Machine Intelligence, Edición pp. 3079-3090, vol. 43, 2021, ISSN 1939-3539
Editor: IEEE Computer Society
DOI: 10.1109/tpami.2021.3067763

Neural Architecture Search: A Survey

Autores: Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank
Publicado en: JMLR, Edición 5, 2019, ISSN 1533-7928
Editor: JMLR

Fast Bayesian hyperparameteroptimization on large datasets

Autores: Aaron Klein Stefan Falkner Simon Bartels Philipp Hennig Frank Hutter
Publicado en: Electronic Journal of Statistics, 2017, ISSN 1935-7524
Editor: Institute of Mathematical Statistics

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Autores: Marius Lindauer, Katharina Eggensperger, Matthias Feurer, Andre Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, Rene Sass, Frank Hutter
Publicado en: Journal of Machine Learning Research, Edición 23, 2022, ISSN 1533-7928
Editor: online

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

Autores: 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
Publicado en: IEEE Transactions on Pattern Analysis and Machine Intelligence, Edición 43/9, 2021, Página(s) 3108-3125, ISSN 0162-8828
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2021.3075372

Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow

Autores: Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox
Publicado en: Computer Vision – ECCV 2018 - 15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part VII, Edición 11211, 2018, Página(s) 677-693, ISBN 978-3-030-01233-5
Editor: Springer International Publishing
DOI: 10.1007/978-3-030-01234-2_40

Automated Machine Learning: Methods, Systems, Challenges

Autores: Hutter, Frank, Kotthoff, Lars, Vanschoren, Joaquin (Eds.)
Publicado en: The Springer Series on Challenges in Machine Learning, 2019
Editor: Springer Switzerland

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