Frank Hutter

Name Venue Year citations
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. JMLR 2022 7
Sample-Efficient Automated Deep Reinforcement Learning. ICLR 2021 13
Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL. TPAMI 2021 11
Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019. TPAMI 2021 2
Well-tuned Simple Nets Excel on Tabular Datasets. NIPS/NeurIPS 2021 6
Learning Heuristic Selection with Dynamic Algorithm Configuration. ICAPS 2021 8
DACBench: A Benchmark Library for Dynamic Algorithm Configuration. IJCAI 2021 6
TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation. ICCV 2021 5
OpenML-Python: an extensible Python API for OpenML. JMLR 2021 30
DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization. IJCAI 2021 10
Smooth Variational Graph Embeddings for Efficient Neural Architecture Search. IJCNN 2021 5
Self-Paced Context Evaluation for Contextual Reinforcement Learning. ICML 2021 4
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning. AISTATS 2021 24
Bayesian Optimization with a Prior for the Optimum. ECML/PKDD 2021 4
TempoRL: Learning When to Act. ICML 2021 3
How Powerful are Performance Predictors in Neural Architecture Search? NIPS/NeurIPS 2021 0
NAS-Bench-x11 and the Power of Learning Curves. NIPS/NeurIPS 2021 0
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift. NIPS/NeurIPS 2021 0
Understanding and Robustifying Differentiable Architecture Search. ICLR 2020 179
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search. ICLR 2020 87
Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework. ECAI 2020 24
Meta-Learning of Neural Architectures for Few-Shot Learning. CVPR 2020 35
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. ICLR 2020 23
Transferring Optimality Across Data Distributions via Homotopy Methods. ICLR 2020 2
Pitfalls and Best Practices in Algorithm Configuration. JAIR 2019 29
Neural Architecture Search: A Survey. JMLR 2019 1151
NAS-Bench-101: Towards Reproducible Neural Architecture Search. ICML 2019 267
An Evolution Strategy with Progressive Episode Lengths for Playing Games. IJCAI 2019 5
AutoDispNet: Improving Disparity Estimation With AutoML. ICCV 2019 40
Meta-Surrogate Benchmarking for Hyperparameter Optimization. NIPS/NeurIPS 2019 24
Optimizing Neural Networks for Patent Classification. ECML/PKDD 2019 9
Maximizing acquisition functions for Bayesian optimization. NIPS/NeurIPS 2018 96
Hyperparameter Importance Across Datasets. KDD 2018 106
Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow. ECCV 2018 107
Warmstarting of Model-Based Algorithm Configuration. AAAI 2018 41
BOHB: Robust and Efficient Hyperparameter Optimization at Scale. ICML 2018 493
Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari. IJCAI 2018 56
Neural Networks for Predicting Algorithm Runtime Distributions. IJCAI 2018 10
Efficient benchmarking of algorithm configurators via model-based surrogates. MLJ 2018 0
The Configurable SAT Solver Challenge (CSSC). Artificial Intelligence 2017 68
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. AISTATS 2017 343
Efficient Parameter Importance Analysis via Ablation with Surrogates. AAAI 2017 24
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA. JMLR 2017 482
AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract). IJCAI 2017 8
Bayesian Optimization with Robust Bayesian Neural Networks. NIPS/NeurIPS 2016 274
Automatic bone parameter estimation for skeleton tracking in optical motion capture. ICRA 2016 13
Bayesian Optimization in a Billion Dimensions via Random Embeddings. JAIR 2016 243
ASlib: A benchmark library for algorithm selection. Artificial Intelligence 2016 159
Efficient and Robust Automated Machine Learning. NIPS/NeurIPS 2015 1071
On the Effective Configuration of Planning Domain Models. IJCAI 2015 38
AutoFolio: An Automatically Configured Algorithm Selector. JAIR 2015 94
SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers. SAT 2015 18
Automatic Configuration of Sequential Planning Portfolios. AAAI 2015 48
Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract). IJCAI 2015 54
Efficient Benchmarking of Hyperparameter Optimizers via Surrogates. AAAI 2015 88
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves. IJCAI 2015 403
Initializing Bayesian Hyperparameter Optimization via Meta-Learning. AAAI 2015 296
Improved Features for Runtime Prediction of Domain-Independent Planners. ICAPS 2014 45
An Efficient Approach for Assessing Hyperparameter Importance. ICML 2014 250
Algorithm runtime prediction: Methods & evaluation. Artificial Intelligence 2014 326
Bayesian Optimization in High Dimensions via Random Embeddings. IJCAI 2013 256
Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms. KDD 2013 1067
Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors. SAT 2012 92
Automated Configuration of Mixed Integer Programming Solvers. CPAIOR 2010 172
ParamILS: An Automatic Algorithm Configuration Framework. JAIR 2009 77
SATzilla: Portfolio-based Algorithm Selection for SAT. JAIR 2008 847
: The Design and Analysis of an Algorithm Portfolio for SAT. CP 2007 139
Automatic Algorithm Configuration Based on Local Search. AAAI 2007 307
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms. CP 2006 194
Efficient Stochastic Local Search for MPE Solving. IJCAI 2005 51
Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT. CP 2002 237
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