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

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

In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.

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

Improving Deep Learning Optimization through Constrained Parameter Regularization Inproceedings

In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.

Helli, Kai; Schnurr, David; Hollmann, Noah; Müller, Samuel; Hutter, Frank

Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data Inproceedings

In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.

Robertson, Jake; Schmidt, Thorsten; Hutter, Frank; Awad, Noor

A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes Inproceedings

In: Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24), 2024.

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

HPO-RL-Bench: A Zero-Cost Benchmark for HPO in Reinforcement Learning Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, 2024, (Runner up for the best paper award).

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

Weight-Entanglement Meets Gradient-Based Neural Architecture Search Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, 2024.

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

Is Mamba Capable of In-Context Learning? Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, 2024.

Salinas, David; Erickson, Nick

TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, 2024.

Watanabe, Shuhei; Mallik, Neeratyoy; Bergman, Edward; Hutter, Frank

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

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, 2024.

Bergman, Eddie; Purucker, Lennart; Hutter, Frank

Don’t Waste Your Time: Early Stopping Cross-Validation Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, 2024.

Kadlecová, Gabriela; Lukasik, Jovita; Pilát, Martin; Vidnerová, Petra; Safari, Mahmoud; Neruda, Roman; Hutter, Frank

Surprisingly Strong Performance Prediction with Neural Graph Features Inproceedings

In: Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.

Rakotoarison, Herilalaina; Adriaensen, Steven; Mallik, Neeratyoy; Garibov, Samir; Bergman, Eddie; Hutter, Frank

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization Inproceedings

In: Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.

Lindauer, Marius; Karl, Florian; Klier, Anne; Moosbauer, Julia; Tornede, Alexander; Mueller, Andreas C; Hutter, Frank; Feurer, Matthias; Bischl, Bernd

Position: A Call to Action for a Human-Centered AutoML Paradigm Inproceedings

In: Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.

Hvarfner, Carl; Hutter, Frank; Nardi, Luigi

A General Framework for User-Guided Bayesian Optimization Inproceedings

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

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.

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.

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, (Oral Paper - top 2% of accepted papers).

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.

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.

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.

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.

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.

Sukthanker, Rhea Sanjay; Zela, Arber; Staffler, Benedikt; Klein, Aaron; Purucker, Lennart; Franke, Joerg K. H.; Hutter, Frank

HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models Inproceedings

In: 38th Conference on Neural Information Processing Systems (NeurIPS), DBT Track, 2024.

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).

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.

Ferreira, Fabio; Schlageter, Moreno; Rajan, Raghu; Biedenkapp, André; Hutter, Frank

One-shot World Models Using a Transformer Trained on a Synthetic Prior Inproceedings

In: NeurIPS 2024 Workshop on Open-World Agents, 2024.

Küken, Jaris; Purucker, Lennart; Hutter, Frank

Large Language Models Engineer Too Many Simple Features for Tabular Data Inproceedings

In: NeurIPS 2024 Third Table Representation Learning Workshop, 2024, (Oral Presentation).

Arango, Sebastian Pineda; Janowski, Maciej; Purucker, Lennart; Zela, Arber; Hutter, Frank; Grabocka, Josif

Ensembling Finetuned Language Models for Text Classification Inproceedings

In: NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles and Scalability, 2024.

Mallik, Neeratyoy; Janowski, Maciej; Hog, Johannes; Rakotoarison, Herilalaina; Klein, Aaron; Grabocka, Josif; Hutter, Frank

Warmstarting for Scaling Language Models Inproceedings

In: NeurIPS 2024 Workshop Adaptive Foundation Models, 2024.

Bhethanabhotla, Sathya Kamesh; Swelam, Omar; Siems, Julien; Salinas, David; Hutter, Frank

Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models Inproceedings

In: NeurIPS 2024 TSALM Workshop, 2024, (Spotlight Presentation).

Sukthanker, Rhea Sanjay; Staffler, Benedikt; Hutter, Frank; Klein, Aaron

Large Language Model Compression with Neural Architecture Search Inproceedings

In: NeurIPS 2024 Workshop on Machine Learning and Compression, 2024.

Müller, Andreas; Siems, Julien; Nori, Harsha; Salinas, David; Zela, Arber; Caruana, Rich; Hutter, Frank

GAMformer: Exploring In-Context Learning for Generalized Additive Models Inproceedings

In: NeurIPS 2024 TRL Workshop, 2024.

Hoo, Shi Bin; Müller, Samuel; Salinas, David; Hutter, Frank

The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features Inproceedings

In: NeurIPS 2024 TRL Workshop, 2024.

Grazzi, Riccardo; Siems, Julien; Franke, Jörg K. H.; Zela, Arber; Hutter, Frank; Pontil, Massimiliano

Unlocking State-Tracking in linear RNNs through Negative Eigenvalues Inproceedings

In: NeurIPS 2024 Workshop on Mathematics of Modern Machine Learning Workshop (M3L), 2024, (Oral Presentation).

Strangmann, Tobias; Purucker, Lennart; Franke, Jörg K. H.; Rapant, Ivo; Ferreira, Fabio; Hutter, Frank

Transfer Learning for Finetuning Large Language Models Inproceedings

In: NeurIPS 2024 Workshop on Adaptive Foundation Models, 2024.

Bordne, Philipp; Hasan, M. Asif; Bergman, Eddie; Awad, Noor; Biedenkapp, André

CANDID DAC: Leveraging Coupled Action Dimensions with Importance Differences in DAC Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Strack, Lukas; Safari, Mahmoud; Hutter, Frank

Towards Efficient Search for Customized Activation Functions With Gradient Descent Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Geburek, Anton Merlin; Mallik, Neeratyoy; Stoll, Danny; Bouthillier, Xavier; Hutter, Frank

LMEMs for post-hoc analysis of HPO Benchmarking Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Rapant, Ivo; Purucker, Lennart; Ferreira, Fabio; Arango, Sebastian Pineda; Kadra, Arlind; Grabocka, Josif; Hutter, Frank

Quick-Tune-Tool: A Practical Tool and its User Guide for Automatically Finetuning Pretrained Models Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Karakasli, Goktug; Adriaensen, Steven; Hutter, Frank

NOSBench-101: Towards Reproducible Neural Optimizer Search Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Helli, Kai; Schnurr, David; Hollmann, Noah; Müller, Samuel; Hutter, Frank

Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Carstensen, Timur; Elsken, Thomas; Rapp, Martin

In-Context Learning for Latency Estimation Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Krishnakumar, Arjun; Jha, Abhash Kumar; Moradian, Shakiba; Rapp, Martin; Hutter, Frank

LoRA-DARTS: Low Rank Adaptation for Differentiable Architecture Search Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Rakotoarison, Herilalaina; Adriaensen, Steven; Mallik, Neeratyoy; Garibov, Samir; Bergman, Edward; Hutter, Frank

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Viering, Tom Julian; Adriaensen, Steven; Rakotoarison, Herilalaina; Hutter, Frank

From Epoch to Sample Size: Developing New Data-driven Priors for Learning Curve Prior-Fitted Networks Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Birinxhiku, Lum; Stoll, Danny; Schrodi, Simon; Hutter, Frank

Beyond Graph-Based Modeling for Hierarchical Neural Architecture Search Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Blauth, Simon; Bürger, Tobias; Häringer, Zacharias; Franke, Jörg K. H.; Hutter, Frank

Fast Optimizer Benchmark Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

Maier, Jannis; Möller, Felix; Purucker, Lennart

Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and Cost Inproceedings

In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024.

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.

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.

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.

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.

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.

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.

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

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.