Name Venue Year citations
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. JAIR 2024 0
PFNs4BO: In-Context Learning for Bayesian Optimization. ICML 2023 0
Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator. IJCAI 2023 0
PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces. IJCAI 2023 0
c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization. IJCAI 2023 0
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks. NIPS/NeurIPS 2023 0
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars. NIPS/NeurIPS 2023 0
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering. NIPS/NeurIPS 2023 0
Self-Correcting Bayesian Optimization through Bayesian Active Learning. NIPS/NeurIPS 2023 0
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition. NIPS/NeurIPS 2023 0
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning. NIPS/NeurIPS 2023 0
Gray-Box Gaussian Processes for Automated Reinforcement Learning. ICLR 2023 0
Transfer NAS with Meta-learned Bayesian Surrogates. ICLR 2023 0
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second. ICLR 2023 0
MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning. JAIR 2023 0
Zero-shot AutoML with Pretrained Models. ICML 2022 0
Learning Synthetic Environments and Reward Networks for Reinforcement Learning. ICLR 2022 0
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. JAIR 2022 28
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy. ICLR 2022 10
Automated Dynamic Algorithm Configuration. JAIR 2022 2
Efficient Automated Deep Learning for Time Series Forecasting. ECML/PKDD 2022 0
Joint Entropy Search For Maximally-Informed Bayesian Optimization. NIPS/NeurIPS 2022 0
NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies. NIPS/NeurIPS 2022 0
JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search. NIPS/NeurIPS 2022 0
Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design. NIPS/NeurIPS 2022 0
Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks. ICLR 2022 0
Transformers Can Do Bayesian Inference. ICLR 2022 0
$\pi$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization. ICLR 2022 0
T3VIP: Transformation-based 3D Video Prediction. IROS 2022 0
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. JMLR 2022 0
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning. JMLR 2022 0
DACBench: A Benchmark Library for Dynamic Algorithm Configuration. IJCAI 2021 12
Well-tuned Simple Nets Excel on Tabular Datasets. NIPS/NeurIPS 2021 43
NAS-Bench-x11 and the Power of Learning Curves. NIPS/NeurIPS 2021 10
Self-Paced Context Evaluation for Contextual Reinforcement Learning. ICML 2021 7
DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization. IJCAI 2021 34
Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL. TPAMI 2021 30
How Powerful are Performance Predictors in Neural Architecture Search? NIPS/NeurIPS 2021 50
Bayesian Optimization with a Prior for the Optimum. ECML/PKDD 2021 17
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning. AISTATS 2021 51
TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation. ICCV 2021 46
TempoRL: Learning When to Act. ICML 2021 8
Smooth Variational Graph Embeddings for Efficient Neural Architecture Search. IJCNN 2021 0
Learning Heuristic Selection with Dynamic Algorithm Configuration. ICAPS 2021 0
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift. NIPS/NeurIPS 2021 0
Sample-Efficient Automated Deep Reinforcement Learning. ICLR 2021 0
Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019. TPAMI 2021 0
OpenML-Python: an extensible Python API for OpenML. JMLR 2021 0
Transferring Optimality Across Data Distributions via Homotopy Methods. ICLR 2020 2
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search. ICLR 2020 116
Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework. ECAI 2020 36
Meta-Learning of Neural Architectures for Few-Shot Learning. CVPR 2020 0
Understanding and Robustifying Differentiable Architecture Search. ICLR 2020 0
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. ICLR 2020 0
AutoDispNet: Improving Disparity Estimation With AutoML. ICCV 2019 52
Meta-Surrogate Benchmarking for Hyperparameter Optimization. NIPS/NeurIPS 2019 32
NAS-Bench-101: Towards Reproducible Neural Architecture Search. ICML 2019 384
An Evolution Strategy with Progressive Episode Lengths for Playing Games. IJCAI 2019 6
Optimizing Neural Networks for Patent Classification. ECML/PKDD 2019 13
Pitfalls and Best Practices in Algorithm Configuration. JAIR 2019 0
Neural Architecture Search: A Survey. JMLR 2019 0
BOHB: Robust and Efficient Hyperparameter Optimization at Scale. ICML 2018 682
Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari. IJCAI 2018 73
Maximizing acquisition functions for Bayesian optimization. NIPS/NeurIPS 2018 147
Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow. ECCV 2018 144
Warmstarting of Model-Based Algorithm Configuration. AAAI 2018 0
Neural Networks for Predicting Algorithm Runtime Distributions. IJCAI 2018 0
Hyperparameter Importance Across Datasets. KDD 2018 0
Efficient benchmarking of algorithm configurators via model-based surrogates. MLJ 2018 0
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA. JMLR 2017 575
AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract). IJCAI 2017 8
Efficient Parameter Importance Analysis via Ablation with Surrogates. AAAI 2017 31
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. AISTATS 2017 0
The Configurable SAT Solver Challenge (CSSC). Artificial Intelligence 2017 0
Bayesian Optimization with Robust Bayesian Neural Networks. NIPS/NeurIPS 2016 343
Automatic bone parameter estimation for skeleton tracking in optical motion capture. ICRA 2016 14
Bayesian Optimization in a Billion Dimensions via Random Embeddings. JAIR 2016 0
ASlib: A benchmark library for algorithm selection. Artificial Intelligence 2016 0
Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract). IJCAI 2015 60
On the Effective Configuration of Planning Domain Models. IJCAI 2015 39
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves. IJCAI 2015 494
Efficient and Robust Automated Machine Learning. NIPS/NeurIPS 2015 1313
Efficient Benchmarking of Hyperparameter Optimizers via Surrogates. AAAI 2015 106
SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers. SAT 2015 19
Initializing Bayesian Hyperparameter Optimization via Meta-Learning. AAAI 2015 364
AutoFolio: An Automatically Configured Algorithm Selector. JAIR 2015 115
Automatic Configuration of Sequential Planning Portfolios. AAAI 2015 53
Improved Features for Runtime Prediction of Domain-Independent Planners. ICAPS 2014 51
An Efficient Approach for Assessing Hyperparameter Importance. ICML 2014 329
Algorithm runtime prediction: Methods & evaluation. Artificial Intelligence 2014 0
Bayesian Optimization in High Dimensions via Random Embeddings. IJCAI 2013 302
Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms. KDD 2013 0
Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors. SAT 2012 103
Automated Configuration of Mixed Integer Programming Solvers. CPAIOR 2010 186
ParamILS: An Automatic Algorithm Configuration Framework. JAIR 2009 992
SATzilla: Portfolio-based Algorithm Selection for SAT. JAIR 2008 915
Automatic Algorithm Configuration Based on Local Search. AAAI 2007 325
: The Design and Analysis of an Algorithm Portfolio for SAT. CP 2007 142
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms. CP 2006 202
Efficient Stochastic Local Search for MPE Solving. IJCAI 2005 51
Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT. CP 2002 240
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