Our ICML 2024 Publications – Machine Learning Lab

Main Track

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.

Workshops

Robertson, Jake; Hollmann, Noah; Awad, Noor; Hutter, Frank

FairPFN: Transformers Can do Counterfactual Fairness Conference

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

Sukthanker, Rhea Sanjay; Zela, Arber; Staffler, Benedikt; Dooley, Samuel; Grabocka, Josif; Hutter, Frank

Multi-objective Differentiable Neural Architecture Search Conference

2nd Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization (WANT@ICML), 2024.

Patil, Sharat; Schirrmeister, Robin Tibor; Ball, Tonio; Hutter, Frank

CoordConformer: Heterogenous EEG datasets decoding using Transformers Conference

Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM@ICML), 2024.