Frank Hutter
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
95
Venues
22
Active years
2002–2025
Best venue rank
A*
Where they publish
Papers
95 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Beyond Random Augmentations: Pretraining with Hard Views. | Fabio Ferreira, Ivo Rapant, Jrg K. H. Franke, Frank Hutter |
| 2025 | ICLR | Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues. | Riccardo Grazzi, Julien Siems, Arber Zela, Jrg K. H. Franke, Frank Hutter, Massimiliano Pontil |
| 2025 | ICLR | KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks. | Dominik Scheuer, Frederic Runge, Jrg K. H. Franke, Michael T. Wolfinger, Christoph Flamm, Frank Hutter |
| 2025 | ICLR | Diffusion-based Neural Network Weights Generation. | Bedionita Soro, Bruno Andreis, Hayeon Lee, Wonyong Jeong, Song Chong, Frank Hutter, Sung Ju Hwang |
| 2025 | ICLR | Multi-objective Differentiable Neural Architecture Search. | Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler, Samuel Dooley, Josif Grabocka, Frank Hutter |
| 2025 | ICML | Position: The Future of Bayesian Prediction Is Prior-Fitted. | Samuel Mller, Arik Reuter, Noah Hollmann, David Rgamer, Frank Hutter |
| 2025 | ICML | Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks. | Dongwoo Lee, Dong Bok Lee, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Frank Hutter, Seon Joo Kim, Hae Beom Lee |
| 2025 | ICML | FairPFN: A Tabular Foundation Model for Causal Fairness. | Jake Robertson, Noah Hollmann, Samuel Mller, Noor H. Awad, Frank Hutter |
| 2025 | ICML | Tuning LLM Judge Design Decisions for 1/1000 of the Cost. | David Salinas, Omar Swelam, Frank Hutter |
| 2024 | AIES | A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes. | Jake Robertson, Thorsten Schmidt, Frank Hutter, Noor H. Awad |
| 2024 | CVPR | DAFT: Data-Aware Fine-Tuning of Foundation Models for Efficient and Effective Medical Image Segmentation. | Alexander Pfefferle, Lennart Purucker, Frank Hutter |
| 2024 | ICLR | A General Framework for User-Guided Bayesian Optimization. | Carl Hvarfner, Frank Hutter, Luigi Nardi |
| 2024 | ICLR | Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How. | Sebastian Pineda-Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka |
| 2024 | ICML | Surprisingly Strong Performance Prediction with Neural Graph Features. | Gabriela Kadlecov, Jovita Lukasik, Martin Pilt, Petra Vidnerov, Mahmoud Safari, Roman Neruda, Frank Hutter |
| 2024 | ICML | Position: A Call to Action for a Human-Centered AutoML Paradigm. | Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas Mller, Frank Hutter, Matthias Feurer, Bernd Bischl |
| 2024 | ICML | In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization. | Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik, Samir Garibov, Eddie Bergman, Frank Hutter |
| 2023 | ICLR | TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second. | Noah Hollmann, Samuel Mller, Katharina Eggensperger, Frank Hutter |
| 2023 | ICLR | Gray-Box Gaussian Processes for Automated Reinforcement Learning. | Gresa Shala, Andr Biedenkapp, Frank Hutter, Josif Grabocka |
| 2023 | ICLR | Transfer NAS with Meta-learned Bayesian Surrogates. | Gresa Shala, Thomas Elsken, Frank Hutter, Josif Grabocka |
| 2023 | ICML | PFNs4BO: In-Context Learning for Bayesian Optimization. | Samuel Mller, Matthias Feurer, Noah Hollmann, Frank Hutter |
| 2023 | IJCAI | 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 |
| 2023 | IJCAI | PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces. | Shuhei Watanabe, Archit Bansal, Frank Hutter |
| 2023 | IJCAI | c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization. | Shuhei Watanabe, Frank Hutter |
| 2023 | IDA | Mind the Gap: Measuring Generalization Performance Across Multiple Objectives. | Matthias Feurer, Katharina Eggensperger, Edward Bergman, Florian Pfisterer, Bernd Bischl, Frank Hutter |
| 2022 | GECCO | Theory-inspired parameter control benchmarks for dynamic algorithm configuration. | Andr Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr |
| 2022 | ICLR | Transformers Can Do Bayesian Inference. | Samuel Mller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter |
| 2022 | ICLR | Learning Synthetic Environments and Reward Networks for Reinforcement Learning. | Fabio Ferreira, Thomas Nierhoff, Andreas Slinger, Frank Hutter |
| 2022 | ICLR | $\pi$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization. | Carl Hvarfner, Danny Stoll, Artur L. F. Souza, Marius Lindauer, Frank Hutter, Luigi Nardi |
| 2022 | ICLR | 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 |
| 2022 | ICLR | 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 |
| 2022 | ICML | Zero-shot AutoML with Pretrained Models. | Ekrem ztrk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter |
| 2022 | IROS | T3VIP: Transformation-based 3D Video Prediction. | Iman Nematollahi, Erick Rosete-Beas, Seyed Mahdi B. Azad, Raghu Rajan, Frank Hutter, Wolfram Burgard |
| 2021 | AISTATS | On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning. | Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan O. Lambert, Andr Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra |
| 2021 | ICCV | TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation. | Samuel G. Mller, Frank Hutter |
| 2021 | ICLR | Sample-Efficient Automated Deep Reinforcement Learning. | Jrg K. H. Franke, Gregor Khler, Andr Biedenkapp, Frank Hutter |
| 2021 | ICML | TempoRL: Learning When to Act. | Andr Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer |
| 2021 | ICML | Self-Paced Context Evaluation for Contextual Reinforcement Learning. | Theresa Eimer, Andr Biedenkapp, Frank Hutter, Marius Lindauer |
| 2021 | IJCAI | DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization. | Noor H. Awad, Neeratyoy Mallik, Frank Hutter |
| 2021 | IJCAI | DACBench: A Benchmark Library for Dynamic Algorithm Configuration. | Theresa Eimer, Andr Biedenkapp, Maximilian Reimer, Steven Adriaensen, Frank Hutter, Marius Lindauer |
| 2021 | IJCNN | Smooth Variational Graph Embeddings for Efficient Neural Architecture Search. | Jovita Lukasik, David Friede, Arber Zela, Frank Hutter, Margret Keuper |
| 2020 | CVPR | Meta-Learning of Neural Architectures for Few-Shot Learning. | Thomas Elsken, Benedikt Staffler, Jan Hendrik Metzen, Frank Hutter |
| 2020 | ECAI | Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework. | Andr Biedenkapp, H. Furkan Bozkurt, Theresa Eimer, Frank Hutter, Marius Lindauer |
| 2020 | ICLR | Transferring Optimality Across Data Distributions via Homotopy Methods. | Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter |
| 2020 | ICLR | Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. | Michael Volpp, Lukas P. Frhlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel |
| 2020 | ICLR | Understanding and Robustifying Differentiable Architecture Search. | Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, Frank Hutter |
| 2020 | ICLR | NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search. | Arber Zela, Julien Siems, Frank Hutter |
| 2020 | PPSN | Learning Step-Size Adaptation in CMA-ES. | Gresa Shala, Andr Biedenkapp, Noor H. Awad, Steven Adriaensen, Marius Lindauer, Frank Hutter |
| 2019 | DIS | Hyperparameter Importance for Image Classification by Residual Neural Networks. | Abhinav Sharma, Jan N. van Rijn, Frank Hutter, Andreas Mller |
| 2019 | ICCV | AutoDispNet: Improving Disparity Estimation With AutoML. | Tonmoy Saikia, Yassine Marrakchi, Arber Zela, Frank Hutter, Thomas Brox |
| 2019 | ICLR | Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution. | Thomas Elsken, Jan Hendrik Metzen, Frank Hutter |
| 2019 | ICLR | Decoupled Weight Decay Regularization. | Ilya Loshchilov, Frank Hutter |
| 2019 | ICLR | Learning to Design RNA. | Frederic Runge, Danny Stoll, Stefan Falkner, Frank Hutter |
| 2019 | ICML | NAS-Bench-101: Towards Reproducible Neural Architecture Search. | Chris Ying, Aaron Klein, Eric Christiansen, Esteban Real, Kevin Murphy, Frank Hutter |
| 2019 | IJCAI | An Evolution Strategy with Progressive Episode Lengths for Playing Games. | Lior Fuks, Noor H. Awad, Frank Hutter, Marius Lindauer |
| 2018 | AAAI | Warmstarting of Model-Based Algorithm Configuration. | Marius Lindauer, Frank Hutter |
| 2018 | ECCV | Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow. | Eddy Ilg, zgn iek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox |
| 2018 | GECCO | Summary of evolutionary computation for wind farm layout optimization. | Dennis G. Wilson, Silvio Rodrigues, Carlos Segura, Ilya Loshchilov, Frank Hutter, Guillermo Lpez Buenfil, Ahmed Kheiri, Ed Keedwell, Mario Ocampo-Pineda, Ender zcan, Sergio Ivvan Valdez Pea, Brian Goldman, Salvador Botello Rionda, Arturo Hernndez Aguirre, Kalyan Veeramachaneni, Sylvain Cussat-Blanc |
| 2018 | ICLR | Simple and efficient architecture search for Convolutional Neural Networks. | Thomas Elsken, Jan Hendrik Metzen, Frank Hutter |
| 2018 | ICLR | Practical Hyperparameter Optimization for Deep Learning. | Stefan Falkner, Aaron Klein, Frank Hutter |
| 2018 | ICML | BOHB: Robust and Efficient Hyperparameter Optimization at Scale. | Stefan Falkner, Aaron Klein, Frank Hutter |
| 2018 | IJCAI | Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari. | Patryk Chrabaszcz, Ilya Loshchilov, Frank Hutter |
| 2018 | IJCAI | Neural Networks for Predicting Algorithm Runtime Distributions. | Katharina Eggensperger, Marius Lindauer, Frank Hutter |
| 2018 | IDA | 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 |
| 2018 | KDD | Hyperparameter Importance Across Datasets. | Jan N. van Rijn, Frank Hutter |
| 2017 | AAAI | Efficient Parameter Importance Analysis via Ablation with Surrogates. | Andre Biedenkapp, Marius Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett, Holger H. Hoos |
| 2017 | AISTATS | Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. | Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter |
| 2017 | ICLR | Learning Curve Prediction with Bayesian Neural Networks. | Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter |
| 2017 | ICLR | SGDR: Stochastic Gradient Descent with Warm Restarts. | Ilya Loshchilov, Frank Hutter |
| 2017 | IJCAI | AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract). | Marius Lindauer, Frank Hutter, Holger H. Hoos, Torsten Schaub |
| 2016 | ICML | Towards Automatically-Tuned Neural Networks. | Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Frank Hutter |
| 2016 | ICRA | Automatic bone parameter estimation for skeleton tracking in optical motion capture. | Tobias Schubert, Katharina Eggensperger, Alexis Gkogkidis, Frank Hutter, Tonio Ball, Wolfram Burgard |
| 2015 | AAAI | Efficient Benchmarking of Hyperparameter Optimizers via Surrogates. | Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2015 | AAAI | Initializing Bayesian Hyperparameter Optimization via Meta-Learning. | Matthias Feurer, Jost Tobias Springenberg, Frank Hutter |
| 2015 | AAAI | AutoFolio: Algorithm Configuration for Algorithm Selection. | Marius Lindauer, Holger H. Hoos, Frank Hutter, Torsten Schaub |
| 2015 | AAAI | Automatic Configuration of Sequential Planning Portfolios. | Jendrik Seipp, Silvan Sievers, Malte Helmert, Frank Hutter |
| 2015 | IJCAI | Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves. | Tobias Domhan, Jost Tobias Springenberg, Frank Hutter |
| 2015 | IJCAI | Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract). | Frank Hutter, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown |
| 2015 | IJCAI | On the Effective Configuration of Planning Domain Models. | Mauro Vallati, Frank Hutter, Luks Chrpa, Thomas Leo McCluskey |
| 2015 | SAT | SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers. | Stefan Falkner, Marius Lindauer, Frank Hutter |
| 2014 | ECAI | Surrogate Benchmarks for Hyperparameter Optimization. | Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2014 | ECAI | Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters. | Matthias Feurer, Jost Tobias Springenberg, Frank Hutter |
| 2014 | ECAI | Bayesian Optimization for More Automatic Machine Learning. | Frank Hutter |
| 2014 | ICML | An Efficient Approach for Assessing Hyperparameter Importance. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2013 | GECCO | An evaluation of sequential model-based optimization for expensive blackbox functions. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2013 | IJCAI | Bayesian Optimization in High Dimensions via Random Embeddings. | Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, Nando de Freitas |
| 2013 | KDD | Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms. | Chris Thornton, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2012 | SAT | Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors. | Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2010 | CPAIOR | Automated Configuration of Mixed Integer Programming Solvers. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2009 | GECCO | An experimental investigation of model-based parameter optimisation: SPO and beyond. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy |
| 2007 | AAAI | Automatic Algorithm Configuration Based on Local Search. | Frank Hutter, Holger H. Hoos, Thomas Sttzle |
| 2007 | CP | : The Design and Analysis of an Algorithm Portfolio for SAT. | Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2007 | FMCAD | Boosting Verification by Automatic Tuning of Decision Procedures. | Frank Hutter, Domagoj Babic, Holger H. Hoos, Alan J. Hu |
| 2006 | CP | Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms. | Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevin Leyton-Brown |
| 2005 | IJCAI | Efficient Stochastic Local Search for MPE Solving. | Frank Hutter, Holger H. Hoos, Thomas Sttzle |
| 2002 | CP | Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT. | Frank Hutter, Dave A. D. Tompkins, Holger H. Hoos |