Machine Learning Lab

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

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

In: The Twelfth International Conference on Learning Representations, 2024, (Oral Presentation).

Hvarfner, Carl; Hellsten, Erik Orm; Hutter, Frank; Nardi, Luigi

Self-Correcting Bayesian Optimization through Bayesian Active Learning Inproceedings

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Dooley*, Samuel; Sukthanker*, Rhea Sanjay; Dickerson, John P; White, Colin; Hutter, Frank; Goldblum, Micah

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023, (Oral Paper - top 2% of accepted papers).

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

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

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

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Adriaensen, Steven; Rakotoarison, Herilalaina; Müller, Samuel; Hutter, Frank

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Hollmann, Noah; Müller, Samuel; Hutter, Frank

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Müller, Samuel; Feurer, Matthias; Hollmann, Noah; Hutter, Frank

PFNs4BO: In-Context Learning for Bayesian Optimization Inproceedings

In: ICML 23, 2023.

Shala, Gresa; Elsken, Thomas; Hutter, Frank; Grabocka, Josif

Transfer NAS with Meta-learned Bayesian Surrogates Inproceedings

In: The Eleventh International Conference on Learning Representations, 2023, (top 5% of accepted papers).

Shala, Gresa; Biedenkapp, André; Hutter, Frank; Grabocka, Josif

Gray-Box Gaussian Processes for Automated Reinforcement Learning Inproceedings

In: Eleventh International Conference on Learning Representations (ICLR'23), 2023.

Hollmann, Noah; Müller, Samuel; Eggensperger, Katharina; Hutter, Frank

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

In: The Eleventh International Conference on Learning Representations, 2023, ( top-25% of accepted papers ).

Kohli, Ravin; Feurer, Matthias; Eggensperger, Katharina; Bischl, Bernd; Hutter, Frank

Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning Inproceedings

In: Data-centric Machine Learning Research (DMLR) Workshop (ICLR 2024), 2024.

Franke, Jörg; Hefenbrock, Michael; Hutter, Frank

Preserving Principal Subspaces to Reduce Catastrophic Forgetting in Fine-tuning Inproceedings

In: Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) Workshop, 2024.

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

Is Mamba Capable of In-Context Learning? Inproceedings

In: Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) Workshop, 2024.

Hvarfner, Carl; Hutter, Frank; Nardi, Luigi

A General Framework for User-Guided Bayesian Optimization Inproceedings

In: The Twelfth International Conference on Learning Representations, 2024.

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

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

In: The Twelfth International Conference on Learning Representations, 2024, (Oral Presentation).

Franke, Jörg K. H.; Hefenbrock, Michael; Koehler, Gregor; Hutter, Frank

New Horizons in Parameter Regularization: A Constraint Approach Inproceedings

In: OPT2023: 15th Annual Workshop on Optimization for Machine Learning, (NeurIPS 2023), 2023.

Hvarfner, Carl; Hellsten, Erik Orm; Hutter, Frank; Nardi, Luigi

Self-Correcting Bayesian Optimization through Bayesian Active Learning Inproceedings

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Dooley*, Samuel; Sukthanker*, Rhea Sanjay; Dickerson, John P; White, Colin; Hutter, Frank; Goldblum, Micah

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023, (Oral Paper - top 2% of accepted papers).

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

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

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

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Adriaensen, Steven; Rakotoarison, Herilalaina; Müller, Samuel; Hutter, Frank

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Hollmann, Noah; Müller, Samuel; Hutter, Frank

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Siems, Julien; Ditschuneit, Konstantin; Ripken, Winfried; Lindborg, Alma; Schambach, Maximilian; Otterbach, Johannes; Genzel, Martin

Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models Inproceedings

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.

Watanabe, Shuhei; Hutter, Frank

c-TPE: Tree-Structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization Inproceedings

In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23), ijcai.org, 2023.

Watanabe, Shuhei; Awad, Noor; Onishi, Masaki; Hutter, Frank

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

In: Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23), 2023.

Watanabe, Shuhei; Bansal, Archit; Hutter, Frank

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

In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23), 2023.

Müller, Samuel; Feurer, Matthias; Hollmann, Noah; Hutter, Frank

PFNs4BO: In-Context Learning for Bayesian Optimization Inproceedings

In: ICML 23, 2023.

Shala, Gresa; Biedenkapp, André; Hutter, Frank; Grabocka, Josif

Gray-Box Gaussian Processes for Automated Reinforcement Learning Inproceedings

In: Eleventh International Conference on Learning Representations (ICLR'23), 2023.

Shala, Gresa; Elsken, Thomas; Hutter, Frank; Grabocka, Josif

Transfer NAS with Meta-learned Bayesian Surrogates Inproceedings

In: The Eleventh International Conference on Learning Representations, 2023, (top 5% of accepted papers).

Hollmann, Noah; Müller, Samuel; Eggensperger, Katharina; Hutter, Frank

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

In: The Eleventh International Conference on Learning Representations, 2023, ( top-25% of accepted papers ).

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

Mind the Gap: Measuring Generalization Performance Across Multiple Objectives Inproceedings

In: Crémilleux, Bruno; Hess, Sibylle; Nijssen, Siegfried (Ed.): Advances in Intelligent Data Analysis XXI. IDA 2023., pp. 130-142, Springer, Cham, 2023.

Weissteiner, Jakob; Heiss, Jakob; Siems, Julien; Seuken, Sven

Bayesian Optimization based Combinatorial Assignment Inproceedings

In: AAAI 2023, 2023.

Hollmann, Noah; Müller, Samuel; Hutter, Frank

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

In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

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

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

In: Thirty-sixth Conference on Neural Information Processing Systems, 2022, (Featured Paper - top 7.5% of accepted papers).

Shala, Gresa; Arango, Sebastian Pineda; Biedenkapp, André; Hutter, Frank; Grabocka, Josif

AutoRL-Bench 1.0 Inproceedings

In: Workshop on Meta-Learning (MetaLearn@NeurIPS'22), 2022.

Shala, Gresa; Biedenkapp, André; Hutter, Frank; Grabocka, Josif

Gray-Box Gaussian Processes for Automated Reinforcement Learning Inproceedings

In: Workshop on Meta-Learning (MetaLearn@NeurIPS'22), 2022.

Hvarfner, Carl; Hutter, Frank; Nardi, Luigi

Joint Entropy Search For Maximally-Informed Bayesian Optimization Inproceedings

In: Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle; Cho, Kyunghyun (Ed.): Advances in Neural Information Processing Systems (NeurIPS 2022), 2022.

Franke, Jörg; Runge, Frederic; Hutter, Frank

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

In: Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle; Cho, Kyunghyun (Ed.): Advances in Neural Information Processing Systems (NeurIPS 2022), 2022.

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

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

In: Thirty-sixth Conference on Neural Information Processing Systems, 2022.

Purucker, Lennart; Stamm, Felix; Lemmerich, Florian; Beel, Joeran

Estimating the Pruned Search Space Size of Subgroup Discovery Inproceedings

In: 2022 IEEE International Conference on Data Mining (ICDM), 2022.

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

T3VIP: Transformation-based 3D Video Prediction Inproceedings

In: IEEE/RSJ International Conf. on Intelligent Robots and Systems (IROS), 2022.

Weissteiner, Jakob; Heiss, Jakob; Siems, Julien; Seuken, Sven

Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment Inproceedings

In: IJCAI-ECAI, 2022.

Hvarfner, Carl; Hutter, Frank; Nardi, Luigi

Joint Entropy Search For Maximally-Informed Bayesian Optimization Inproceedings

In: Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML@ICML'22), 2022.

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

DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning Inproceedings

In: Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML@ICML'22), 2022.

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

Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration Inproceedings

In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22), 2022, (Won the best paper award in the GECH track).

Biedenkapp, André; Speck, David; Sievers, Silvan; Hutter, Frank; Lindauer, Marius; Seipp, Jendrik

Learning Domain-Independent Policies for Open List Selection Inproceedings

In: Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL @ ICAPS'22), 2022.

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

Zero-shot AutoML with Pretrained Models Inproceedings

In: International Conference on Machine Learning (ICML), 2022.

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

Transformers Can Do Bayesian Inference Inproceedings

In: 10th International Conference on Learning Representations, ICLR 2022, 2022.

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

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

In: International Conference on Learning Representations (ICLR) 2022, 2022.

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

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

In: International Conference on Learning Representations (ICLR), 2022.

Hvarfner, Carl; Stoll, Danny; Souza, Artur; Lindauer, Marius; Hutter, Frank; Nardi, Luigi

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

In: 10th International Conference on Learning Representations, ICLR 2022, OpenReview.net, 2022.

Ferreira, Fabio; Nierhoff, Thomas; Sälinger, Andreas; Hutter, Frank

Learning Synthetic Environments and Reward Networks for Reinforcement Learning Inproceedings

In: 10th International Conference on Learning Representations (ICLR), OpenReview.net, 2022.

Hollmann, Noah; Müller, Samuel; Eggensperger, Katharina; Hutter, Frank

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

In: NeurIPS 2022 First Table Representation Workshop, 2022.

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

Towards Discovering Neural Architectures from Scratch Inproceedings

In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022.

Adriaensen, Steven; Rakotoarison, Herilalaina; Müller, Samuel; Hutter, Frank

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

In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022.

Watanabe, Shuhei; Awad, Noor; Onishi, Masaki; Hutter, Frank

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

In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022.

Sukthanker, Rhea Sanjay; Krishnakumar, Arjun; Patil, Sharat; Hutter, Frank

GraViT-E: Gradient-based Vision Transformer Search with Entangled Weights Inproceedings

In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022.

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

PriorBand: HyperBand + Human Expert Knowledge Inproceedings

In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022.

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

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

In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022.

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

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

In: Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 2022.

Shala, Gresa; Elsken, Thomas; Hutter, Frank; Grabocka, Josif

Transfer NAS with Meta-learned Bayesian Surrogates Inproceedings

In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022.

Watanabe, Shuhei; Hutter, Frank

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

In: NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems, 2022.

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

OpenML Benchmarking Suites Inproceedings

In: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, 2021.

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

CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning Inproceedings

In: Workshop on Ecological Theory of Reinforcement Learning (EcoRL@NeurIPS'21), 2021.

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

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

In: Vanschoren, J.; Yeung, S. (Ed.): Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, 2021.

Awad, Noor; Mallik, Neeratyoy; Hutter, Frank

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

In: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI'21), ijcai.org, 2021.

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

DACBench: A Benchmark Library for Dynamic Algorithm Configuration Inproceedings

In: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI'21), ijcai.org, 2021.

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

Learning Heuristic Selection with Dynamic Algorithm Configuration Inproceedings

In: Proceedings of the 31st International Conference on Automated Planning and Scheduling (ICAPS'21), 2021.

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

Multi-headed Neural Ensemble Search Inproceedings

In: Workshop on Uncertainty and Robustness in Deep Learning (UDL@ICML`21), 2021.

Biedenkapp, André; Rajan, Raghu; Hutter, Frank; Lindauer, Marius

TempoRL: Learning When to Act Inproceedings

In: Proceedings of the 38th International Conference on Machine Learning (ICML 2021), 2021.

Eimer, Theresa; Biedenkapp, André; Hutter, Frank; Lindauer, Marius

Self-Paced Context Evaluations for Contextual Reinforcement Learning Inproceedings

In: Proceedings of the 38th International Conference on Machine Learning (ICML 2021), 2021.

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

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

In: Workshop on Automated Machine Learning (AutoML@ICML'21), 2021.

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

MDP Playground: A Design and Debug Testbed for Reinforcement Learning Inproceedings

In: arXiv:1909.07750, 2021.

Colin White Shen Yan, Yash Savani; Hutter, Frank

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

In: Proceedings of the CVPR 2021 Workshop on Neural Architecture Search (CVPR-NAS '21), 2021.

Kadra, Arlind; Lindauer, Marius; Hutter, Frank; Grabocka, Josif

Well-tuned Simple Nets Excel on Tabular Datasets Inproceedings

In: Thirty-Fifth Conference on Neural Information Processing Systems, 2021.

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

How Powerful are Performance Predictors in Neural Architecture Search? Inproceedings

In: Thirty-Fifth Conference on Neural Information Processing Systems, 2021.

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

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift Inproceedings

In: Thirty-Fifth Conference on Neural Information Processing Systems, 2021.

Yan, Shen; White, Colin; Savani, Yash; Hutter, Frank

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

In: Thirty-Fifth Conference on Neural Information Processing Systems, 2021.

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

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

In: Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS)'21, 2021.

Müller, Samuel; Hutter, Frank

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

In: ICCV, 2021, (Oral Presentation (Top 3%)).

Müller, Samuel; Biedenkapp, André; Hutter, Frank

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

In: AAAI workshop on Meta-Learning Challenges, 2021.

Souza, Artur; Nardi, Luigi; Oliveira, Leonardo; Olukotun, Kunle; Lindauer, Marius; Hutter, Frank

Bayesian Optimization with a Prior for the Optimum Inproceedings

In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2021.

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

Learning Heuristic Selection with Dynamic Algorithm Configuration Inproceedings

In: Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL@ICAPS'20), 2020.

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

Learning Step-Size Adaptation in CMA-ES Inproceedings

In: Proceedings of the Sixteenth International Conference on Parallel Problem Solving from Nature (PPSN'20), 2020.

Biedenkapp, André; Rajan, Raghu; Hutter, Frank; Lindauer, Marius

Towards TempoRL: Learning When to Act Inproceedings

In: Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20), 2020.

Eimer, Theresa; Biedenkapp, André; Hutter, Frank; Lindauer, Marius

Towards Self-Paced Context Evaluations for Contextual Reinforcement Learning Inproceedings

In: Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20), 2020.

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

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

In: Proceedings of the Twenty-fourth European Conference on Artificial Intelligence (ECAI'20), 2020.

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

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

In: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, (Oral Presentation (Top 6%)).

Awad, N; Mallik, N; Hutter, F

Differential Evolution for Neural Architecture Search Inproceedings

In: Proceedings of the 1st workshop on neural architecture search(@ICLR'20), 2020.

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

Transferring Optimally Across Data Distrutions via Homotopy Methods Inproceedings

In: International Conference on Learning Representations, 2020.

Schirrmeister, Robin; Zhou, Yuxuan; Ball, Tonio; Zhang, Dan

Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features Inproceedings

In: Larochelle, H; Ranzato, M; Hadsell, R; Balcan, M F; Lin, H (Ed.): Advances in Neural Information Processing Systems, pp. 21038–21049, Curran Associates, Inc., 2020.

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

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

In: International Conference on Learning Representations, 2020.

Zela, Arber; Siems, Julien; Hutter, Frank

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

In: International Conference on Learning Representations, 2020.

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

Understanding and Robustifying Differentiable Architecture Search Inproceedings

In: International Conference on Learning Representations, 2020, (Oral Presentation (Top 7%)).

Rajan, Raghu; Hutter, Frank

MDP Playground: Meta-Features in Reinforcement Learning Inproceedings

In: NeurIPS 2019 Deep RL Workshop, 2019.

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

Towards White-box Benchmarks for Algorithm Control Inproceedings

In: IJCAI 2019 DSO Workshop, 2019.

Fuks, L; Awad, N; Hutter, F; Lindauer, M

An Evolution Strategy with Progressive Episode Lengths for Playing Games Inproceedings

In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’19), 2019.

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

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

In: IJCAI 2019 DSO Workshop, 2019.

Gargiani, M; Klein, A; Falkner, S; Hutter, F

Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings Inproceedings

In: 6th ICML Workshop on Automated Machine Learning, 2019.

Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank

Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution Inproceedings

In: International Conference on Learning Representations, 2019.

Loshchilov, Ilya; Hutter, Frank

Decoupled Weight Decay Regularization Inproceedings

In: International Conference on Learning Representations, 2019.

Runge, Frederic; Stoll, Danny; Falkner, Stefan; Hutter, Frank

Learning to Design RNA Inproceedings

In: International Conference on Learning Representations, 2019.

Saikia, T; Marrakchi, Y; Zela, A; Hutter, F; Brox, T

AutoDispNet: Improving Disparity Estimation With AutoML Inproceedings

In: IEEE International Conference on Computer Vision (ICCV), 2019.

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

Nas-bench-101: Towards reproducible neural architecture search Inproceedings

In: Thirty-sixth International Conference on Machine Learning, 2019.

Chrabąszcz, Patryk; Loshchilov, Ilya; Hutter, Frank

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

In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18, pp. 1419–1426, International Joint Conferences on Artificial Intelligence Organization, 2018.

Eggensperger, Katharina; Lindauer, Marius; Hutter, Frank

Neural Networks for Predicting Algorithm Runtime Distributions Inproceedings

In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’18), pp. 1442-1448, 2018.

Falkner, Stefan; Klein, Aaron; Hutter, Frank

BOHB: Robust and Efficient Hyperparameter Optimization at Scale Inproceedings

In: Proceedings of the 35th International Conference on Machine Learning (ICML 2018), pp. 1436–1445, 2018.

Feurer, M; Hutter, F

Towards Further Automation in AutoML Inproceedings

In: ICML 2018 AutoML Workshop, 2018.

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

Practical Automated Machine Learning for the AutoML Challenge 2018 Inproceedings

In: ICML 2018 AutoML Workshop, 2018.

Feurer, Matthias; Letham, Benjamin; Bakshy, Eytan

Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles Inproceedings

In: ICML 2018 AutoML Workshop, 2018, (This publication is superseded by the 2022 arXiv preprint Practical Transfer Learning for Bayesian Optimization.).

Schirrmeister, R; Chrabąszcz, P; Hutter, F; Ball, T

Training Generative Reversible Networks Inproceedings

In: ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models, 2018.

Zela, Arber; Klein, Aaron; Falkner, Stefan; Hutter, Frank

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

In: ICML 2018 AutoML Workshop, 2018.

Biedenkapp, André; Marben, Joshua; Lindauer, Marius; Hutter, Frank

CAVE: Configuration Assessment, Visualization and Evaluation Inproceedings

In: Proceedings of the International Conference on Learning and Intelligent Optimization (LION'18), 2018.

Lindauer, M; Hutter, F

Warmstarting of Model-based Algorithm Configuration Inproceedings

In: Proceedings of the AAAI conference, pp. 1355–1362, 2018.

Abdulrahman, S M; Brazdil, P; van Rijn, J N; Vanschoren, J

Speeding up algorithm selection using average ranking and active testing by introducing runtime Inproceedings

In: Machine Learning, pp. 79–108, 2018.

Franke, Jörg; Niehues, Jan; Waibel, Alex

Robust and Scalable Differentiable Neural Computer for Question Answering Inproceedings

In: Proceedings of the Workshop on Machine Reading for Question Answering, pp. 47–59, 2018.

van Rijn, J N; Holmes, G; Pfahringer, B; Vanschoren, J

The online performance estimation framework: heterogeneous ensemble learning for data streams Inproceedings

In: Machine Learning, pp. 149–176, 2018.

Wilson, James; Hutter, Frank; Deisenroth, Marc

Maximizing acquisition functions for Bayesian optimization Inproceedings

In: Bengio, S; Wallach, H; Larochelle, H; Grauman, K; Cesa-Bianchi, N; Garnett, R (Ed.): Advances in Neural Information Processing Systems 31, pp. 9906–9917, Curran Associates, Inc., 2018.

Martinez-Cantin, Ruben; Tee, Kevin; McCourt, Mike; Eggensperger, Katharina

Filtering Outliers in Bayesian Optimization Inproceedings

In: NeuriPS workshop on Bayesian Optimization (BayesOpt'17), 2017.

Falkner, S; Klein, A; Hutter, F

Combining Hyperband and Bayesian Optimization Inproceedings

In: NIPS 2017 Bayesian Optimization Workshop, 2017.

Klein, A; Falkner, S; Mansur, N; Hutter, F

RoBO: A Flexible and Robust Bayesian Optimization Framework in Python Inproceedings

In: NIPS 2017 Bayesian Optimization Workshop, 2017.

Lindauer, Marius; van Rijn, Jan N; Kotthoff, Lars

Open Algorithm Selection Challenge 2017: Setup and Scenarios Inproceedings

In: Lindauer, Marius; van Rijn, Jan N; Kotthoff, Lars (Ed.): Proceedings of the Open Algorithm Selection Challenge, pp. 1–7, PMLR, Brussels, Belgium, 2017.

Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank

Simple And Efficient Architecture Search for Convolutional Neural Networks Inproceedings

In: NIPS Workshop on Meta-Learning, 2017.

Greff, K; Klein, A; Chovanec, M; Hutter, F; Schmidhuber, J

The Sacred Infrastructure for Computational Research Inproceedings

In: Proceedings of the 15th Python in Science Conference (SciPy 2017), 2017.

Lindauer, M; Hoos, H; Hutter, F; Schaub, T

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

In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), 2017.

Klein, A; Falkner, S; Springenberg, J T; Hutter, F

Learning Curve Prediction with Bayesian Neural Networks Inproceedings

In: International Conference on Learning Representations (ICLR) 2017 Conference Track, 2017.

Loshchilov, I; Hutter, F

SGDR: Stochastic Gradient Descent with Warm Restarts Inproceedings

In: International Conference on Learning Representations (ICLR) 2017 Conference Track, 2017.

Wagner, M; Friedrich, T; Lindauer, M

Improving local search in a minimum vertex cover solver for classes of networks Inproceedings

In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2017.

Biedenkapp, André; Lindauer, Marius; Eggensperger, Katharina; Fawcett, Chris; Hoos, Holger H; Hutter, Frank

Efficient Parameter Importance Analysis via Ablation with Surrogates Inproceedings

In: Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI'17), pp. 773–779, 2017.

Wilson, James T.; Moriconi, Riccardo; Hutter, Frank; Deisenroth, Marc P.

The Reparameterization Trick for Acquisition Functions Inproceedings

In: NIPS Workshop on Bayesian Optimization, 2017.

Klein, A; Falkner, S; Bartels, S; Hennig, P; Hutter, F

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets Inproceedings

In: Proceedings of the AISTATS conference, 2017.

Klein, A; Falkner, S; Bartels, S; Hennig, P; Hutter, F

Fast Bayesian hyperparameter optimization on large datasets Inproceedings

In: Electronic Journal of Statistics, 2017.

Müller, Markus; Franke, Jörg; Waibel, Alex; Stüker, Sebastian

Towards phoneme inventory discovery for documentation of unwritten languages Inproceedings

In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5200–5204, IEEE 2017.

van Rijn, J N; Hutter, F

An Empirical Study of Hyperparameter Importance Across Datasets Inproceedings

In: Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms (AutoML 2017), pp. 97–104, 2017.

Springenberg, J T; Klein, A; Falkner, S; Hutter, F

Bayesian optimization with robust Bayesian neural networks Inproceedings

In: Advances in Neural Information Processing Systems 29, 2016.