Frank Hutter

According to our database, Frank Hutter authored at least 238 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML.

Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter

J. Artif. Intell. Res., 2024

Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks.

Shuhei Watanabe, Neeratyoy Mallik, Edward Bergman, Frank Hutter

CoRR, 2024

Multi-objective Differentiable Neural Architecture Search.

Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler, Samuel Dooley, Josif Grabocka, Frank Hutter

CoRR, 2024

Diffusion-based Neural Network Weights Generation.

Bedionita Soro, Bruno Andreis, Hayeon Lee, Song Chong, Frank Hutter, Sung Ju Hwang

CoRR, 2024

TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks.

Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova, Chinmay Hegde, Frank Hutter, Micah Goldblum, Niv Cohen, Colin White

CoRR, 2024

Is Mamba Capable of In-Context Learning?

Riccardo Grazzi, Julien Siems, Simon Schrodi, Thomas Brox, Frank Hutter

CoRR, 2024

Rethinking Performance Measures of RNA Secondary Structure Problems.

Frederic Runge, Jörg K. H. Franke, Daniel Fertmann, Frank Hutter

CoRR, 2024

2023

Neural Architecture Search for Dense Prediction Tasks in Computer Vision.

Rohit Mohan, Thomas Elsken, Arber Zela, Jan Hendrik Metzen, Benedikt Staffler, Thomas Brox, Abhinav Valada, Frank Hutter

Int. J. Comput. Vis., July, 2023

MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information.

Tim Ruhkopf, Aditya Mohan, Difan Deng, Alexander Tornede, Frank Hutter, Marius Lindauer

Trans. Mach. Learn. Res., 2023

MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning.

Raghu Rajan, Jessica Lizeth Borja Diaz, Suresh Guttikonda, Fabio Ferreira, André Biedenkapp, Jan Ole von Hartz, Frank Hutter

J. Artif. Intell. Res., 2023

Weight-Entanglement Meets Gradient-Based Neural Architecture Search.

Rhea Sanjay Sukthanker, Arjun Krishnakumar, Mahmoud Safari, Frank Hutter

CoRR, 2023

A General Framework for User-Guided Bayesian Optimization.

Carl Hvarfner, Frank Hutter, Luigi Nardi

CoRR, 2023

New Horizons in Parameter Regularization: A Constraint Approach.

Jörg K. H. Franke, Michael Hefenbrock, Gregor Köhler, Frank Hutter

CoRR, 2023

Managing AI Risks in an Era of Rapid Progress.

Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila A. McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann

CoRR, 2023

Hard View Selection for Contrastive Learning.

Fabio Ferreira, Ivo Rapant, Frank Hutter

CoRR, 2023

Scalable Deep Learning for RNA Secondary Structure Prediction.

Jörg K. H. Franke, Frederic Runge, Frank Hutter

CoRR, 2023

Towards Automated Design of Riboswitches.

Frederic Runge, Jörg K. H. Franke, Frank Hutter

CoRR, 2023

Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How.

Sebastian Pineda-Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka

CoRR, 2023

PFNs Are Flexible Models for Real-World Bayesian Optimization.

Samuel Müller, Matthias Feurer, Noah Hollmann, Frank Hutter

CoRR, 2023

MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization.

Noor H. Awad, Ayushi Sharma, Philipp Muller, Janek Thomas, Frank Hutter

CoRR, 2023

LLMs for Semi-Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering.

Noah Hollmann, Samuel Müller, Frank Hutter

CoRR, 2023

Neural Architecture Search: Insights from 1000 Papers.

Colin White, Mahmoud Safari, Rhea Sukthanker, Binxin Ru, Thomas Elsken, Arber Zela, Debadeepta Dey, Frank Hutter

CoRR, 2023

Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars.

Simon Schrodi, Danny Stoll, Binxin Ru, Rhea Sukthanker, Thomas Brox, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning.

Neeratyoy Mallik, Edward Bergman, Carl Hvarfner, Danny Stoll, Maciej Janowski, Marius Lindauer, Luigi Nardi, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-Correcting Bayesian Optimization through Bayesian Active Learning.

Carl Hvarfner, Erik Hellsten, Frank Hutter, Luigi Nardi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering.

Noah Hollmann, Samuel Müller, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition.

Samuel Dooley, Rhea Sukthanker, John P. Dickerson, Colin White, Frank Hutter, Micah Goldblum

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks.

Steven Adriaensen, Herilalaina Rakotoarison, Samuel Müller, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization.

Shuhei Watanabe, Frank Hutter

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces.

Shuhei Watanabe, Archit Bansal, Frank Hutter

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator.

Shuhei Watanabe, Noor H. Awad, Masaki Onishi, Frank Hutter

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Mind the Gap: Measuring Generalization Performance Across Multiple Objectives.

Matthias Feurer, Katharina Eggensperger, Edward Bergman, Florian Pfisterer, Bernd Bischl, Frank Hutter

Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

PFNs4BO: In-Context Learning for Bayesian Optimization.

Samuel Müller, Matthias Feurer, Noah Hollmann, Frank Hutter

Proceedings of the International Conference on Machine Learning, 2023

Transfer NAS with Meta-learned Bayesian Surrogates.

Gresa Shala, Thomas Elsken, Frank Hutter, Josif Grabocka

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Gray-Box Gaussian Processes for Automated Reinforcement Learning.

Gresa Shala, André Biedenkapp, Frank Hutter, Josif Grabocka

Proceedings of the Eleventh International Conference on Learning Representations, 2023

TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second.

Noah Hollmann, Samuel Müller, Katharina Eggensperger, Frank Hutter

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.

Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, René Sass, Frank Hutter

J. Mach. Learn. Res., 2022

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

Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter

J. Mach. Learn. Res., 2022

Automated Reinforcement Learning (AutoRL): A Survey and Open Problems.

Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust, Frank Hutter, Marius Lindauer

J. Artif. Intell. Res., 2022

Automated Dynamic Algorithm Configuration.

Steven Adriaensen, André Biedenkapp, Gresa Shala, Noor H. Awad, Theresa Eimer, Marius Lindauer, Frank Hutter

J. Artif. Intell. Res., 2022

Multi-objective Tree-structured Parzen Estimator Meets Meta-learning.

Shuhei Watanabe, Noor H. Awad, Masaki Onishi, Frank Hutter

CoRR, 2022

c-TPE: Generalizing Tree-structured Parzen Estimator with Inequality Constraints for Continuous and Categorical Hyperparameter Optimization.

Shuhei Watanabe, Frank Hutter

CoRR, 2022

Towards Discovering Neural Architectures from Scratch.

Simon Schrodi, Danny Stoll, Binxin Ru, Rhea Sukthanker, Thomas Brox, Frank Hutter

CoRR, 2022

On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition.

Rhea Sukthanker, Samuel Dooley, John P. Dickerson, Colin White, Frank Hutter, Micah Goldblum

CoRR, 2022

On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning.

Diane Wagner, Fabio Ferreira, Danny Stoll, Robin Tibor Schirrmeister, Samuel Müller, Frank Hutter

CoRR, 2022

Meta-Learning a Real-Time Tabular AutoML Method For Small Data.

Noah Hollmann, Samuel Müller, Katharina Eggensperger, Frank Hutter

CoRR, 2022

Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification.

Adrian El Baz, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Shell Hu, Frank Hutter, Zhengying Liu, Felix Mohr, Jan N. van Rijn, Xin Wang, Isabelle Guyon

CoRR, 2022

DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning.

René Sass, Eddie Bergman, André Biedenkapp, Frank Hutter, Marius Lindauer

CoRR, 2022

πBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization.

Carl Hvarfner, Danny Stoll, Artur L. F. Souza, Marius Lindauer, Frank Hutter, Luigi Nardi

CoRR, 2022

Why Do Machine Learning Practitioners Still Use Manual Tuning? A Qualitative Study.

Niklas Hasebrook, Felix Morsbach, Niclas Kannengießer, Jörg K. H. Franke, Frank Hutter, Ali Sunyaev

CoRR, 2022

Neural Architecture Search for Dense Prediction Tasks in Computer Vision.

Thomas Elsken, Arber Zela, Jan Hendrik Metzen, Benedikt Staffler, Thomas Brox, Abhinav Valada, Frank Hutter

CoRR, 2022

Contextualize Me - The Case for Context in Reinforcement Learning.

Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer

CoRR, 2022

Efficient Automated Deep Learning for Time Series Forecasting.

Difan Deng, Florian Karl, Frank Hutter, Bernd Bischl, Marius Lindauer

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies.

Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Joint Entropy Search For Maximally-Informed Bayesian Optimization.

Carl Hvarfner, Frank Hutter, Luigi Nardi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design.

Jörg K. H. Franke, Frederic Runge, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search.

Archit Bansal, Danny Stoll, Maciej Janowski, Arber Zela, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

T3VIP: Transformation-based 3D Video Prediction.

Iman Nematollahi, Erick Rosete-Beas, Seyed Mahdi B. Azad, Raghu Rajan, Frank Hutter, Wolfram Burgard

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Zero-shot AutoML with Pretrained Models.

Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter

Proceedings of the International Conference on Machine Learning, 2022

Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks.

Arber Zela, Julien Niklas Siems, Lucas Zimmer, Jovita Lukasik, Margret Keuper, Frank Hutter

Proceedings of the Tenth International Conference on Learning Representations, 2022

NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy.

Yash Mehta, Colin White, Arber Zela, Arjun Krishnakumar, Guri Zabergja, Shakiba Moradian, Mahmoud Safari, Kaicheng Yu, Frank Hutter

Proceedings of the Tenth International Conference on Learning Representations, 2022

$\pi$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization.

Carl Hvarfner, Danny Stoll, Artur L. F. Souza, Marius Lindauer, Frank Hutter, Luigi Nardi

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Synthetic Environments and Reward Networks for Reinforcement Learning.

Fabio Ferreira, Thomas Nierhoff, Andreas Sälinger, Frank Hutter

Proceedings of the Tenth International Conference on Learning Representations, 2022

Transformers Can Do Bayesian Inference.

Samuel Müller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter

Proceedings of the Tenth International Conference on Learning Representations, 2022

Theory-inspired parameter control benchmarks for dynamic algorithm configuration.

André Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

2021

Automated Configuration and Selection of SAT Solvers.

Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown

Proceedings of the Handbook of Satisfiability - Second Edition, 2021

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

Lucas Zimmer, Marius Lindauer, Frank Hutter

IEEE Trans. Pattern Anal. Mach. Intell., 2021

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

Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Fabio Ferreira, Isabelle Guyon, Sirui Hong, Frank Hutter, Rongrong Ji, Júlio C. S. Jacques Júnior, Ge Li, Marius Lindauer, Zhipeng Luo, Meysam Madadi, Thomas Nierhoff, Kangning Niu, Chunguang Pan, Danny Stoll, Sébastien Treguer, Jin Wang, Peng Wang, Chenglin Wu, Youcheng Xiong, Arber Zela, Yang Zhang

IEEE Trans. Pattern Anal. Mach. Intell., 2021

OpenML-Python: an extensible Python API for OpenML.

Matthias Feurer, Jan N. van Rijn, Arlind Kadra, Pieter Gijsbers, Neeratyoy Mallik, Sahithya Ravi, Andreas Müller, Joaquin Vanschoren, Frank Hutter

J. Mach. Learn. Res., 2021

On the Importance of Domain Model Configuration for Automated Planning Engines.

Mauro Vallati, Lukás Chrpa, Thomas Leo McCluskey, Frank Hutter

J. Autom. Reason., 2021

CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning.

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

CoRR, 2021

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.

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

CoRR, 2021

Multi-headed Neural Ensemble Search.

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

CoRR, 2021

Bag of Tricks for Neural Architecture Search.

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

CoRR, 2021

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

Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka

CoRR, 2021

Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization.

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

CoRR, 2021

How Powerful are Performance Predictors in Neural Architecture Search?

Colin White, Arber Zela, Binxin Ru, Yang Liu, Frank Hutter

CoRR, 2021

In-Loop Meta-Learning with Gradient-Alignment Reward.

Samuel Müller, André Biedenkapp, Frank Hutter

CoRR, 2021

Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies.

Fabio Ferreira, Thomas Nierhoff, Frank Hutter

CoRR, 2021

Bayesian Optimization with a Prior for the Optimum.

Artur L. F. Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift.

Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

NAS-Bench-x11 and the Power of Learning Curves.

Shen Yan, Colin White, Yash Savani, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Powerful are Performance Predictors in Neural Architecture Search?

Colin White, Arber Zela, Robin Ru, Yang Liu, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale.

Nicholas Roberts, Samuel Guo, Cong Xu, Ameet Talwalkar, David Lander, Lvfang Tao, Linhang Cai, Shuaicheng Niu, Jianyu Heng, Hongyang Qin, Minwen Deng, Johannes Hog, Alexander Pfefferle, Sushil Ammanaghatta Shivakumar, Arjun Krishnakumar, Yubo Wang, Rhea Sukthanker, Frank Hutter, Euxhen Hasanaj, Tien-Dung Le, Mikhail Khodak, Yuriy Nevmyvaka, Kashif Rasul, Frederic Sala, Anderson Schneider, Junhong Shen, Evan R. Sparks

Proceedings of the NeurIPS 2022 Competition Track, 2021

Well-tuned Simple Nets Excel on Tabular Datasets.

Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Katharina Eggensperger, Philipp Müller, Neeratyoy Mallik, Matthias Feurer, René Sass, Aaron Klein, Noor H. Awad, Marius Lindauer, Frank Hutter

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

OpenML Benchmarking Suites.

Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Pieter Gijsbers, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan N. van Rijn, Joaquin Vanschoren

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification.

Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy M. Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search.

Jovita Lukasik, David Friede, Arber Zela, Frank Hutter, Margret Keuper

Proceedings of the International Joint Conference on Neural Networks, 2021

DACBench: A Benchmark Library for Dynamic Algorithm Configuration.

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

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

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

Noor H. Awad, Neeratyoy Mallik, Frank Hutter

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Self-Paced Context Evaluation for Contextual Reinforcement Learning.

Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer

Proceedings of the 38th International Conference on Machine Learning, 2021

TempoRL: Learning When to Act.

André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer

Proceedings of the 38th International Conference on Machine Learning, 2021

Sample-Efficient Automated Deep Reinforcement Learning.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

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

Samuel G. Müller, Frank Hutter

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

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

Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan O. Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning Heuristic Selection with Dynamic Algorithm Configuration.

David Speck, André Biedenkapp, Frank Hutter, Robert Mattmüller, Marius Lindauer

Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021

2020

Machine-learning-based diagnostics of EEG pathology.

Lukas Alexander Wilhelm Gemein, Robin Tibor Schirrmeister, Patryk Chrabaszcz, Daniel Wilson, Joschka Boedecker, Andreas Schulze-Bonhage, Frank Hutter, Tonio Ball

NeuroImage, 2020

Squirrel: A Switching Hyperparameter Optimizer.

Noor H. Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter

CoRR, 2020

Differential Evolution for Neural Architecture Search.

Noor H. Awad, Neeratyoy Mallik, Frank Hutter

CoRR, 2020

Convergence Analysis of Homotopy-SGD for non-convex optimization.

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

CoRR, 2020

Hyperparameter Transfer Across Developer Adjustments.

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

CoRR, 2020

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search.

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

CoRR, 2020

Neural Model-based Optimization with Right-Censored Observations.

Katharina Eggensperger, Kai Haase, Philipp Müller, Marius Lindauer, Frank Hutter

CoRR, 2020

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

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

CoRR, 2020

Auto-Sklearn 2.0: The Next Generation.

Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter

CoRR, 2020

Prior-guided Bayesian Optimization.

Artur L. F. Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter

CoRR, 2020

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

Lucas Zimmer, Marius Lindauer, Frank Hutter

CoRR, 2020

Neural Ensemble Search for Performant and Calibrated Predictions.

Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh

CoRR, 2020

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

Matilde Gargiani, Andrea Zanelli, Moritz Diehl, Frank Hutter

CoRR, 2020

The locality dilemma of Sankoff-like RNA alignments.

Teresa Müller, Milad Miladi, Frank Hutter, Ivo L. Hofacker, Sebastian Will, Rolf Backofen

Bioinform., 2020

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.

Joel Lehman, Jeff Clune, Dusan Misevic, Christoph Adami, Lee Altenberg, Julie Beaulieu, Peter J. Bentley, Samuel Bernard, Guillaume Beslon, David M. Bryson, Nick Cheney, Patryk Chrabaszcz, Antoine Cully, Stéphane Doncieux, Fred C. Dyer, Kai Olav Ellefsen, Robert Feldt, Stephan Fischer, Stephanie Forrest, Antoine Frénoy, Christian Gagné, Léni K. Le Goff, Laura M. Grabowski, Babak Hodjat, Frank Hutter, Laurent Keller, Carole Knibbe, Peter Krcah, Richard E. Lenski, Hod Lipson, Robert MacCurdy, Carlos Maestre, Risto Miikkulainen, Sara Mitri, David E. Moriarty, Jean-Baptiste Mouret, Anh Nguyen, Charles Ofria, Marc Parizeau, David P. Parsons, Robert T. Pennock, William F. Punch, Thomas S. Ray, Marc Schoenauer, Eric Schulte, Karl Sims, Kenneth O. Stanley, François Taddei, Danesh Tarapore, Simon Thibault, Richard A. Watson, Westley Weimer, Jason Yosinski

Artif. Life, 2020

Learning Step-Size Adaptation in CMA-ES.

Gresa Shala, André Biedenkapp, Noor H. Awad, Steven Adriaensen, Marius Lindauer, Frank Hutter

Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

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

Arber Zela, Julien Siems, Frank Hutter

Proceedings of the 8th International Conference on Learning Representations, 2020

Understanding and Robustifying Differentiable Architecture Search.

Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, Frank Hutter

Proceedings of the 8th International Conference on Learning Representations, 2020

Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization.

Michael Volpp, Lukas P. Fröhlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel

Proceedings of the 8th International Conference on Learning Representations, 2020

Transferring Optimality Across Data Distributions via Homotopy Methods.

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

Proceedings of the 8th International Conference on Learning Representations, 2020

Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework.

André Biedenkapp, H. Furkan Bozkurt, Theresa Eimer, Frank Hutter, Marius Lindauer

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Meta-Learning of Neural Architectures for Few-Shot Learning.

Thomas Elsken, Benedikt Staffler, Jan Hendrik Metzen, Frank Hutter

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Neural Architecture Search: A Survey.

Thomas Elsken, Jan Hendrik Metzen, Frank Hutter

J. Mach. Learn. Res., 2019

Pitfalls and Best Practices in Algorithm Configuration.

Katharina Eggensperger, Marius Lindauer, Frank Hutter

J. Artif. Intell. Res., 2019

Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control.

Jörg K. H. Franke, Gregor Köhler, Noor H. Awad, Frank Hutter

CoRR, 2019

Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings.

Matilde Gargiani, Aaron Klein, Stefan Falkner, Frank Hutter

CoRR, 2019

!MDP Playground: Meta-Features in Reinforcement Learning.

Raghu Rajan, Frank Hutter

CoRR, 2019

Best Practices for Scientific Research on Neural Architecture Search.

Marius Lindauer, Frank Hutter

CoRR, 2019

BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters.

Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Joshua Marben, Philipp Müller, Frank Hutter

CoRR, 2019

Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters.

Marius Lindauer, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Frank Hutter

CoRR, 2019

Towards White-box Benchmarks for Algorithm Control.

André Biedenkapp, H. Furkan Bozkurt, Frank Hutter, Marius Lindauer

CoRR, 2019

Tabular Benchmarks for Joint Architecture and Hyperparameter Optimization.

Aaron Klein, Frank Hutter

CoRR, 2019

Meta-Learning Acquisition Functions for Bayesian Optimization.

Michael Volpp, Lukas P. Fröhlich, Andreas Doerr, Frank Hutter, Christian Daniel

CoRR, 2019

Optimizing Neural Networks for Patent Classification.

Louay Abdelgawad, Peter Kluegl, Erdan Genc, Stefan Falkner, Frank Hutter

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Meta-Surrogate Benchmarking for Hyperparameter Optimization.

Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An Evolution Strategy with Progressive Episode Lengths for Playing Games.

Lior Fuks, Noor H. Awad, Frank Hutter, Marius Lindauer

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

NAS-Bench-101: Towards Reproducible Neural Architecture Search.

Chris Ying, Aaron Klein, Eric Christiansen, Esteban Real, Kevin Murphy, Frank Hutter

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning to Design RNA.

Frederic Runge, Danny Stoll, Stefan Falkner, Frank Hutter

Proceedings of the 7th International Conference on Learning Representations, 2019

Decoupled Weight Decay Regularization.

Ilya Loshchilov, Frank Hutter

Proceedings of the 7th International Conference on Learning Representations, 2019

Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution.

Thomas Elsken, Jan Hendrik Metzen, Frank Hutter

Proceedings of the 7th International Conference on Learning Representations, 2019

AutoDispNet: Improving Disparity Estimation With AutoML.

Tonmoy Saikia, Yassine Marrakchi, Arber Zela, Frank Hutter, Thomas Brox

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Hyperparameter Importance for Image Classification by Residual Neural Networks.

Abhinav Sharma, Jan N. van Rijn, Frank Hutter, Andreas Müller

Proceedings of the Discovery Science - 22nd International Conference, 2019

Towards Automatically-Tuned Deep Neural Networks.

Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Matthias Urban, Michael Burkart, Maximilian Dippel, Marius Lindauer, Frank Hutter

Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA.

Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown

Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Auto-sklearn: Efficient and Robust Automated Machine Learning.

Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter

Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Hyperparameter Optimization.

Matthias Feurer, Frank Hutter

Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Neural Architecture Search.

Thomas Elsken, Jan Hendrik Metzen, Frank Hutter

Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

2018

Efficient benchmarking of algorithm configurators via model-based surrogates.

Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown

Mach. Learn., 2018

A case study of algorithm selection for the traveling thief problem.

Markus Wagner, Marius Lindauer, Mustafa Misir, Samadhi Nallaperuma, Frank Hutter

J. Heuristics, 2018

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

Arber Zela, Aaron Klein, Stefan Falkner, Frank Hutter

CoRR, 2018

Generative Reversible Networks.

Robin Tibor Schirrmeister, Patryk Chrabaszcz, Frank Hutter, Tonio Ball

CoRR, 2018

Multi-objective Architecture Search for CNNs.

Thomas Elsken, Jan Hendrik Metzen, Frank Hutter

CoRR, 2018

Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks.

Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox

CoRR, 2018

Maximizing acquisition functions for Bayesian optimization.

James T. Wilson, Frank Hutter, Marc Peter Deisenroth

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

CAVE: Configuration Assessment, Visualization and Evaluation.

Andre Biedenkapp, Joshua Marben, Marius Lindauer, Frank Hutter

Proceedings of the Learning and Intelligent Optimization - 12th International Conference, 2018

Hyperparameter Importance Across Datasets.

Jan N. van Rijn, Frank Hutter

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Neural Networks for Predicting Algorithm Runtime Distributions.

Katharina Eggensperger, Marius Lindauer, Frank Hutter

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari.

Patryk Chrabaszcz, Ilya Loshchilov, Frank Hutter

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Don't Rule Out Simple Models Prematurely: A Large Scale Benchmark Comparing Linear and Non-linear Classifiers in OpenML.

Benjamin Strang, Peter van der Putten, Jan N. van Rijn, Frank Hutter

Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

BOHB: Robust and Efficient Hyperparameter Optimization at Scale.

Stefan Falkner, Aaron Klein, Frank Hutter

Proceedings of the 35th International Conference on Machine Learning, 2018

Practical Hyperparameter Optimization for Deep Learning.

Stefan Falkner, Aaron Klein, Frank Hutter

Proceedings of the 6th International Conference on Learning Representations, 2018

Simple and efficient architecture search for Convolutional Neural Networks.

Thomas Elsken, Jan Hendrik Metzen, Frank Hutter

Proceedings of the 6th International Conference on Learning Representations, 2018

Summary of evolutionary computation for wind farm layout optimization.

Dennis G. Wilson, Silvio Rodrigues, Carlos Segura, Ilya Loshchilov, Frank Hutter, Guillermo López Buenfil, Ahmed Kheiri, Ed Keedwell, Mario Ocampo-Pineda, Ender Özcan, Sergio Iwan Valdez Pea, Brian Goldman, Salvador Botello Rionda, Arturo Hernández Aguirre, Kalyan Veeramachaneni, Sylvain Cussat-Blanc

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow.

Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox

Proceedings of the Computer Vision - ECCV 2018, 2018

Warmstarting of Model-Based Algorithm Configuration.

Marius Lindauer, Frank Hutter

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Selection and Configuration of Parallel Portfolios.

Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown

Proceedings of the Handbook of Parallel Constraint Reasoning., 2018

2017

Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA.

Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown

J. Mach. Learn. Res., 2017

The reparameterization trick for acquisition functions.

James T. Wilson, Riccardo Moriconi, Frank Hutter, Marc Peter Deisenroth

CoRR, 2017

Fixing Weight Decay Regularization in Adam.

Ilya Loshchilov, Frank Hutter

CoRR, 2017

Predicting Runtime Distributions using Deep Neural Networks.

Katharina Eggensperger, Marius Lindauer, Frank Hutter

CoRR, 2017

Deep learning with convolutional neural networks for decoding and visualization of EEG pathology.

Robin Tibor Schirrmeister, Lukas Gemein, Katharina Eggensperger, Frank Hutter, Tonio Ball

CoRR, 2017

OpenML Benchmarking Suites and the OpenML100.

Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan N. van Rijn, Joaquin Vanschoren

CoRR, 2017

Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG.

Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer, Martin Glasstetter, Katharina Eggensperger, Michael Tangermann, Frank Hutter, Wolfram Burgard, Tonio Ball

CoRR, 2017

Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates.

Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown

CoRR, 2017

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

Patryk Chrabaszcz, Ilya Loshchilov, Frank Hutter

CoRR, 2017

The Configurable SAT Solver Challenge (CSSC).

Frank Hutter, Marius Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos, Kevin Leyton-Brown

Artif. Intell., 2017

The Sacred Infrastructure for Computational Research.

Klaus Greff, Aaron Klein, Martin Chovanec, Frank Hutter, Jürgen Schmidhuber

Proceedings of the 16th Python in Science Conference 2017, 2017

An Empirical Study of Hyperparameter Importance Across Datasets.

Jan N. van Rijn, Frank Hutter

Proceedings of the International Workshop on Automatic Selection, 2017

OASC-2017: *Zilla Submission.

Chris Cameron, Holger H. Hoos, Kevin Leyton-Brown, Frank Hutter

Proceedings of the Open Algorithm Selection Challenge 2017, 2017

AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract).

Marius Lindauer, Frank Hutter, Holger H. Hoos, Torsten Schaub

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

SGDR: Stochastic Gradient Descent with Warm Restarts.

Ilya Loshchilov, Frank Hutter

Proceedings of the 5th International Conference on Learning Representations, 2017

Learning Curve Prediction with Bayesian Neural Networks.

Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter

Proceedings of the 5th International Conference on Learning Representations, 2017

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets.

Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Efficient Parameter Importance Analysis via Ablation with Surrogates.

Andre Biedenkapp, Marius Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett, Holger H. Hoos

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Bayesian Optimization in a Billion Dimensions via Random Embeddings.

Ziyu Wang, Frank Hutter, Masrour Zoghi, David Matheson, Nando de Freitas

J. Artif. Intell. Res., 2016

Asynchronous Stochastic Gradient MCMC with Elastic Coupling.

Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter

CoRR, 2016

SGDR: Stochastic Gradient Descent with Restarts.

Ilya Loshchilov, Frank Hutter

CoRR, 2016

CMA-ES for Hyperparameter Optimization of Deep Neural Networks.

Ilya Loshchilov, Frank Hutter

CoRR, 2016

ASlib: A benchmark library for algorithm selection.

Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren

Artif. Intell., 2016

Bayesian Optimization with Robust Bayesian Neural Networks.

Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

An Empirical Study of Per-instance Algorithm Scheduling.

Marius Lindauer, Rolf-David Bergdoll, Frank Hutter

Proceedings of the Learning and Intelligent Optimization - 10th International Conference, 2016

Automatic bone parameter estimation for skeleton tracking in optical motion capture.

Tobias Schubert, Katharina Eggensperger, Alexis Gkogkidis, Frank Hutter, Tonio Ball, Wolfram Burgard

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Towards Automatically-Tuned Neural Networks.

Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Frank Hutter

Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016

2015

Beyond Manual Tuning of Hyperparameters.

Frank Hutter, Jörg Lücke, Lars Schmidt-Thieme

Künstliche Intell., 2015

AutoFolio: An Automatically Configured Algorithm Selector.

Marius Lindauer, Holger H. Hoos, Frank Hutter, Torsten Schaub

J. Artif. Intell. Res., 2015

Online Batch Selection for Faster Training of Neural Networks.

Ilya Loshchilov, Frank Hutter

CoRR, 2015

SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers.

Stefan Falkner, Marius Lindauer, Frank Hutter

Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2015, 2015

Efficient and Robust Automated Machine Learning.

Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

From Sequential Algorithm Selection to Parallel Portfolio Selection.

Marius Lindauer, Holger H. Hoos, Frank Hutter

Proceedings of the Learning and Intelligent Optimization - 9th International Conference, 2015

On the Effective Configuration of Planning Domain Models.

Mauro Vallati, Frank Hutter, Lukás Chrpa, Thomas Leo McCluskey

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract).

Frank Hutter, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves.

Tobias Domhan, Jost Tobias Springenberg, Frank Hutter

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Automatic Configuration of Sequential Planning Portfolios.

Jendrik Seipp, Silvan Sievers, Malte Helmert, Frank Hutter

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

AutoFolio: Algorithm Configuration for Algorithm Selection.

Marius Lindauer, Holger H. Hoos, Frank Hutter, Torsten Schaub

Proceedings of the Algorithm Configuration, 2015

Initializing Bayesian Hyperparameter Optimization via Meta-Learning.

Matthias Feurer, Jost Tobias Springenberg, Frank Hutter

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Efficient Benchmarking of Hyperparameter Optimizers via Surrogates.

Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Understanding the empirical hardness of <i>NP</i>-complete problems.

Kevin Leyton-Brown, Holger H. Hoos, Frank Hutter, Lin Xu

Commun. ACM, 2014

Algorithm runtime prediction: Methods & evaluation.

Frank Hutter, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown

Artif. Intell., 2014

AClib: A Benchmark Library for Algorithm Configuration.

Frank Hutter, Manuel López-Ibáñez, Chris Fawcett, Marius Lindauer, Holger H. Hoos, Kevin Leyton-Brown, Thomas Stützle

Proceedings of the Learning and Intelligent Optimization, 2014

Algorithm Configuration in the Cloud: A Feasibility Study.

Daniel Geschwender, Frank Hutter, Lars Kotthoff, Yuri Malitsky, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Learning and Intelligent Optimization, 2014

An Efficient Approach for Assessing Hyperparameter Importance.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the 31th International Conference on Machine Learning, 2014

Bayesian Optimization for More Automatic Machine Learning.

Frank Hutter

Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters.

Matthias Feurer, Jost Tobias Springenberg, Frank Hutter

Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

Surrogate Benchmarks for Hyperparameter Optimization.

Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

Improved Features for Runtime Prediction of Domain-Independent Planners.

Chris Fawcett, Mauro Vallati, Frank Hutter, Jörg Hoffmann, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, 2014

2013

A Kernel for Hierarchical Parameter Spaces.

Frank Hutter, Michael A. Osborne

CoRR, 2013

Bayesian Optimization With Censored Response Data.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

CoRR, 2013

Identifying Key Algorithm Parameters and Instance Features Using Forward Selection.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Learning and Intelligent Optimization - 7th International Conference, 2013

Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms.

Chris Thornton, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Bayesian Optimization in High Dimensions via Random Embeddings.

Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, Nando de Freitas

Proceedings of the IJCAI 2013, 2013

An evaluation of sequential model-based optimization for expensive blackbox functions.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

2012

Algorithm Runtime Prediction: The State of the Art

Frank Hutter, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown

CoRR, 2012

Auto-WEKA: Automated Selection and Hyper-Parameter Optimization of Classification Algorithms

Chris Thornton, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

CoRR, 2012

Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors.

Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2012, 2012

Parallel Algorithm Configuration.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012

2011

Sequential Model-Based Optimization for General Algorithm Configuration.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Learning and Intelligent Optimization - 5th International Conference, 2011

2010

Tradeoffs in the empirical evaluation of competing algorithm designs.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Ann. Math. Artif. Intell., 2010

Time-Bounded Sequential Parameter Optimization.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy

Proceedings of the Learning and Intelligent Optimization, 4th International Conference, 2010

Automated Configuration of Mixed Integer Programming Solvers.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 2010

Sequential Model-Based Parameter Optimization: an Experimental Investigation of Automated and Interactive Approaches.

Frank Hutter, Thomas Bartz-Beielstein, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy

Proceedings of the Experimental Methods for the Analysis of Optimization Algorithms., 2010

2009

ParamILS: An Automatic Algorithm Configuration Framework.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Thomas Stützle

J. Artif. Intell. Res., 2009

An experimental investigation of model-based parameter optimisation: SPO and beyond.

Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy

Proceedings of the Genetic and Evolutionary Computation Conference, 2009

2008

SATzilla: Portfolio-based Algorithm Selection for SAT.

Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

J. Artif. Intell. Res., 2008

2007

Boosting Verification by Automatic Tuning of Decision Procedures.

Frank Hutter, Domagoj Babic, Holger H. Hoos, Alan J. Hu

Proceedings of the Formal Methods in Computer-Aided Design, 7th International Conference, 2007

: The Design and Analysis of an Algorithm Portfolio for SAT.

Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Principles and Practice of Constraint Programming, 2007

Automatic Algorithm Configuration Based on Local Search.

Frank Hutter, Holger H. Hoos, Thomas Stützle

Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006

Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program.

Wolfgang Achtner, Esma Aïmeur, Sarabjot Singh Anand, Douglas E. Appelt, Naveen Ashish, Tiffany Barnes, Joseph E. Beck, M. Bernardine Dias, Prashant Doshi, Chris Drummond, William Elazmeh, Ariel Felner, Dayne Freitag, Hector Geffner, Christopher W. Geib, Richard Goodwin, Robert C. Holte, Frank Hutter, Fair Isaac, Nathalie Japkowicz, Gal A. Kaminka, Sven Koenig, Michail G. Lagoudakis, David B. Leake, Lundy Lewis, Hugo Liu, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Pascal Poupart, David V. Pynadath, Thomas Roth-Berghofer, Wheeler Ruml, Stefan Schulz, Sven Schwarz, Stephanie Seneff, Amit P. Sheth, Ron Sun, Michael Thielscher, Afzal Upal, Jason D. Williams, Steve J. Young, Dmitry Zelenko

AI Mag., 2006

Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms.

Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevin Leyton-Brown

Proceedings of the Principles and Practice of Constraint Programming, 2006

2005

Efficient Stochastic Local Search for MPE Solving.

Frank Hutter, Holger H. Hoos, Thomas Stützle

Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

2004

Diagnosis by a waiter and a Mars explorer.

Nando de Freitas, Richard Dearden, Frank Hutter, Rubén Morales-Menéndez, Jim Mutch, David Poole

Proc. IEEE, 2004

2002

Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT.

Frank Hutter, Dave A. D. Tompkins, Holger H. Hoos

Proceedings of the Principles and Practice of Constraint Programming, 2002