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.

[BibT_eX]

[DOI]

Jörg K. H. Franke

Frederic Runge

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

Zero-shot AutoML with Pretrained Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

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

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

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

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

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

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Synthetic Environments and Reward Networks for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Transformers Can Do Bayesian Inference.

[BibT_eX]

[DOI]

Samuel Müller

Noah Hollmann

Sebastian Pineda-Arango

Josif Grabocka

Proceedings of the Tenth International Conference on Learning Representations, 2022

Theory-inspired parameter control benchmarks for dynamic algorithm configuration.

[BibT_eX]

[DOI]

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

2021

Automated Configuration and Selection of SAT Solvers.

[BibT_eX]

[DOI]

Proceedings of the Handbook of Satisfiability - Second Edition, 2021

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

[BibT_eX]

[DOI]

Lucas Zimmer

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

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

[BibT_eX]

[DOI]

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

OpenML-Python: an extensible Python API for OpenML.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

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

[BibT_eX]

[DOI]

J. Autom. Reason., 2021

CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

Multi-headed Neural Ensemble Search.

[BibT_eX]

[DOI]

Ashwin Raaghav Narayanan

CoRR, 2021

Bag of Tricks for Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

How Powerful are Performance Predictors in Neural Architecture Search?

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

Samuel Müller

André Biedenkapp

CoRR, 2021

Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies.

[BibT_eX]

[DOI]

Fabio Ferreira

Thomas Nierhoff

CoRR, 2021

Bayesian Optimization with a Prior for the Optimum.

[BibT_eX]

[DOI]

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

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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?

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the NeurIPS 2022 Competition Track, 2021

Well-tuned Simple Nets Excel on Tabular Datasets.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

OpenML Benchmarking Suites.

[BibT_eX]

[DOI]

Rafael Gomes Mantovani

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.

[BibT_eX]

[DOI]

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

DACBench: A Benchmark Library for Dynamic Algorithm Configuration.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Noor H. Awad

Neeratyoy Mallik

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

Self-Paced Context Evaluation for Contextual Reinforcement Learning.

[BibT_eX]

[DOI]

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

TempoRL: Learning When to Act.

[BibT_eX]

[DOI]

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

Sample-Efficient Automated Deep Reinforcement Learning.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Samuel G. Müller

Lukas Alexander Wilhelm Gemein

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

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

[BibT_eX]

[DOI]

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

Learning Heuristic Selection with Dynamic Algorithm Configuration.

[BibT_eX]

[DOI]

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

2020

Machine-learning-based diagnostics of EEG pathology.

[BibT_eX]

[DOI]

Daniel Wilson

Joschka Boedecker

Andreas Schulze-Bonhage

Tonio Ball

NeuroImage, 2020

Squirrel: A Switching Hyperparameter Optimizer.

[BibT_eX]

[DOI]

CoRR, 2020

Differential Evolution for Neural Architecture Search.

[BibT_eX]

[DOI]

Noor H. Awad

Neeratyoy Mallik

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Hyperparameter Transfer Across Developer Adjustments.

[BibT_eX]

[DOI]

CoRR, 2020

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search.

[BibT_eX]

[DOI]

Jovita Lukasik

David Friede

Arber Zela

Heiner Stuckenschmidt

Margret Keuper

CoRR, 2020

Neural Model-based Optimization with Right-Censored Observations.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Auto-Sklearn 2.0: The Next Generation.

[BibT_eX]

[DOI]

CoRR, 2020

Prior-guided Bayesian Optimization.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

Lucas Zimmer

CoRR, 2020

Neural Ensemble Search for Performant and Calibrated Predictions.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

The locality dilemma of Sankoff-like RNA alignments.

[BibT_eX]

[DOI]

Bioinform., 2020

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

[BibT_eX]

[DOI]

Artif. Life, 2020

Learning Step-Size Adaptation in CMA-ES.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Arber Zela

Julien Siems

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

Understanding and Robustifying Differentiable Architecture Search.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

Transferring Optimality Across Data Distributions via Homotopy Methods.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

2019

Neural Architecture Search: A Survey.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2019

Pitfalls and Best Practices in Algorithm Configuration.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2019

Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control.

[BibT_eX]

[DOI]

CoRR, 2019

Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings.

[BibT_eX]

[DOI]

CoRR, 2019

!MDP Playground: Meta-Features in Reinforcement Learning.

[BibT_eX]

[DOI]

Raghu Rajan

CoRR, 2019

Best Practices for Scientific Research on Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

André Biedenkapp

CoRR, 2019

Towards White-box Benchmarks for Algorithm Control.

[BibT_eX]

[DOI]

CoRR, 2019

Tabular Benchmarks for Joint Architecture and Hyperparameter Optimization.

[BibT_eX]

[DOI]

CoRR, 2019

Meta-Learning Acquisition Functions for Bayesian Optimization.

[BibT_eX]

[DOI]

CoRR, 2019

Optimizing Neural Networks for Patent Classification.

[BibT_eX]

[DOI]

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

Meta-Surrogate Benchmarking for Hyperparameter Optimization.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

Learning to Design RNA.

[BibT_eX]

[DOI]

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

Decoupled Weight Decay Regularization.

[BibT_eX]

[DOI]

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

Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution.

[BibT_eX]

[DOI]

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

AutoDispNet: Improving Disparity Estimation With AutoML.

[BibT_eX]

[DOI]

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

Hyperparameter Importance for Image Classification by Residual Neural Networks.

[BibT_eX]

[DOI]

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

Towards Automatically-Tuned Deep Neural Networks.

[BibT_eX]

[DOI]

Hector Mendoza

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

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

[BibT_eX]

[DOI]

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

Auto-sklearn: Efficient and Robust Automated Machine Learning.

[BibT_eX]

[DOI]

Manuel Blum

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

Hyperparameter Optimization.

[BibT_eX]

[DOI]

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

Neural Architecture Search.

[BibT_eX]

[DOI]

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

2018

Efficient benchmarking of algorithm configurators via model-based surrogates.

[BibT_eX]

[DOI]

Mach. Learn., 2018

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

[BibT_eX]

[DOI]

J. Heuristics, 2018

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

[BibT_eX]

[DOI]

CoRR, 2018

Generative Reversible Networks.

[BibT_eX]

[DOI]

Tonio Ball

CoRR, 2018

Multi-objective Architecture Search for CNNs.

[BibT_eX]

[DOI]

CoRR, 2018

Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Maximizing acquisition functions for Bayesian optimization.

[BibT_eX]

[DOI]

James T. Wilson

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.

[BibT_eX]

[DOI]

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

Hyperparameter Importance Across Datasets.

[BibT_eX]

[DOI]

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

Neural Networks for Predicting Algorithm Runtime Distributions.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

BOHB: Robust and Efficient Hyperparameter Optimization at Scale.

[BibT_eX]

[DOI]

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

Practical Hyperparameter Optimization for Deep Learning.

[BibT_eX]

[DOI]

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

Simple and efficient architecture search for Convolutional Neural Networks.

[BibT_eX]

[DOI]

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

Summary of evolutionary computation for wind farm layout optimization.

[BibT_eX]

[DOI]

Guillermo López Buenfil

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.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Warmstarting of Model-Based Algorithm Configuration.

[BibT_eX]

[DOI]

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

Selection and Configuration of Parallel Portfolios.

[BibT_eX]

[DOI]

Proceedings of the Handbook of Parallel Constraint Reasoning., 2018

2017

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

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

The reparameterization trick for acquisition functions.

[BibT_eX]

[DOI]

James T. Wilson

Riccardo Moriconi

Marc Peter Deisenroth

CoRR, 2017

Fixing Weight Decay Regularization in Adam.

[BibT_eX]

[DOI]

CoRR, 2017

Predicting Runtime Distributions using Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2017

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

[BibT_eX]

[DOI]

Lukas Gemein

Tonio Ball

CoRR, 2017

OpenML Benchmarking Suites and the OpenML100.

[BibT_eX]

[DOI]

Rafael Gomes Mantovani

Joaquin Vanschoren

CoRR, 2017

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

[BibT_eX]

[DOI]

Lukas Dominique Josef Fiederer

Martin Glasstetter

CoRR, 2017

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

[BibT_eX]

[DOI]

CoRR, 2017

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

[BibT_eX]

[DOI]

CoRR, 2017

The Configurable SAT Solver Challenge (CSSC).

[BibT_eX]

[DOI]

Artif. Intell., 2017

The Sacred Infrastructure for Computational Research.

[BibT_eX]

[DOI]

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

An Empirical Study of Hyperparameter Importance Across Datasets.

[BibT_eX]

[DOI]

Proceedings of the International Workshop on Automatic Selection, 2017

OASC-2017: *Zilla Submission.

[BibT_eX]

[DOI]

Proceedings of the Open Algorithm Selection Challenge 2017, 2017

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

[BibT_eX]

[DOI]

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

SGDR: Stochastic Gradient Descent with Warm Restarts.

[BibT_eX]

[DOI]

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

Learning Curve Prediction with Bayesian Neural Networks.

[BibT_eX]

[DOI]

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

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets.

[BibT_eX]

[DOI]

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

Efficient Parameter Importance Analysis via Ablation with Surrogates.

[BibT_eX]

[DOI]

Andre Biedenkapp

Chris Fawcett

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

2016

Bayesian Optimization in a Billion Dimensions via Random Embeddings.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2016

Asynchronous Stochastic Gradient MCMC with Elastic Coupling.

[BibT_eX]

[DOI]

CoRR, 2016

SGDR: Stochastic Gradient Descent with Restarts.

[BibT_eX]

[DOI]

CoRR, 2016

CMA-ES for Hyperparameter Optimization of Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2016

ASlib: A benchmark library for algorithm selection.

[BibT_eX]

[DOI]

Artif. Intell., 2016

Bayesian Optimization with Robust Bayesian Neural Networks.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Rolf-David Bergdoll

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

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

[BibT_eX]

[DOI]

Tobias Schubert

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

Towards Automatically-Tuned Neural Networks.

[BibT_eX]

[DOI]

Hector Mendoza

Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016

2015

Beyond Manual Tuning of Hyperparameters.

[BibT_eX]

[DOI]

Jörg Lücke

Lars Schmidt-Thieme

Künstliche Intell., 2015

AutoFolio: An Automatically Configured Algorithm Selector.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2015

Online Batch Selection for Faster Training of Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2015

SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers.

[BibT_eX]

[DOI]

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

Efficient and Robust Automated Machine Learning.

[BibT_eX]

[DOI]

Manuel Blum

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.

[BibT_eX]

[DOI]

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

On the Effective Configuration of Planning Domain Models.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Tobias Domhan

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

Automatic Configuration of Sequential Planning Portfolios.

[BibT_eX]

[DOI]

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

AutoFolio: Algorithm Configuration for Algorithm Selection.

[BibT_eX]

[DOI]

Proceedings of the Algorithm Configuration, 2015

Initializing Bayesian Hyperparameter Optimization via Meta-Learning.

[BibT_eX]

[DOI]

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

Efficient Benchmarking of Hyperparameter Optimizers via Surrogates.

[BibT_eX]

[DOI]

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

2014

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

[BibT_eX]

[DOI]

Commun. ACM, 2014

Algorithm runtime prediction: Methods & evaluation.

[BibT_eX]

[DOI]

Artif. Intell., 2014

AClib: A Benchmark Library for Algorithm Configuration.

[BibT_eX]

[DOI]

Proceedings of the Learning and Intelligent Optimization, 2014

Algorithm Configuration in the Cloud: A Feasibility Study.

[BibT_eX]

[DOI]

Proceedings of the Learning and Intelligent Optimization, 2014

An Efficient Approach for Assessing Hyperparameter Importance.

[BibT_eX]

[DOI]

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

Bayesian Optimization for More Automatic Machine Learning.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

2013

A Kernel for Hierarchical Parameter Spaces.

[BibT_eX]

[DOI]

Michael A. Osborne

CoRR, 2013

Bayesian Optimization With Censored Response Data.

[BibT_eX]

[DOI]

CoRR, 2013

Identifying Key Algorithm Parameters and Instance Features Using Forward Selection.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

Bayesian Optimization in High Dimensions via Random Embeddings.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2013, 2013

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

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

2012

Algorithm Runtime Prediction: The State of the Art

[BibT_eX]

[DOI]

CoRR, 2012

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

[BibT_eX]

[DOI]

CoRR, 2012

Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors.

[BibT_eX]

[DOI]

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

Parallel Algorithm Configuration.

[BibT_eX]

[DOI]

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

2011

Sequential Model-Based Optimization for General Algorithm Configuration.

[BibT_eX]

[DOI]

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

2010

Tradeoffs in the empirical evaluation of competing algorithm designs.

[BibT_eX]

[DOI]

Ann. Math. Artif. Intell., 2010

Time-Bounded Sequential Parameter Optimization.

[BibT_eX]

[DOI]

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

Automated Configuration of Mixed Integer Programming Solvers.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Thomas Bartz-Beielstein

Kevin P. Murphy

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

2009

ParamILS: An Automatic Algorithm Configuration Framework.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2009

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

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2009

2008

SATzilla: Portfolio-based Algorithm Selection for SAT.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2008

2007

Boosting Verification by Automatic Tuning of Decision Procedures.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Proceedings of the Principles and Practice of Constraint Programming, 2007

Automatic Algorithm Configuration Based on Local Search.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

AI Mag., 2006

Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Principles and Practice of Constraint Programming, 2006

2005

Efficient Stochastic Local Search for MPE Solving.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Nando de Freitas

Richard Dearden