17.07.2020
MCML at ICML 2020
Two Accepted Papers (2 Workshops)
37th International Conference on Machine Learning, Virtual, Jul 18, 2020
We are happy to announce that MCML researchers have contributed a total of 2 papers to ICML 2020: 2 Workshop papers. Congrats to our researchers!
Workshops (2 papers)
M. Binder • F. Pfisterer • B. Bischl
Collecting empirical data about hyperparameters for data driven AutoML.
AutoML @ICML 2020 - 7th Workshop on Automated Machine Learning at the 37th International Conference on Machine Learning. Virtual, Jul 18, 2020. PDF
Collecting empirical data about hyperparameters for data driven AutoML.
AutoML @ICML 2020 - 7th Workshop on Automated Machine Learning at the 37th International Conference on Machine Learning. Virtual, Jul 18, 2020. PDF
C. Molnar • G. König • J. Herbinger • T. Freiesleben • S. Dandl • C. A. Scholbeck • G. Casalicchio • M. Grosse-Wentrup • B. Bischl
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models.
XXAI @ICML 2020 - Workshop on Extending Explainable AI Beyond Deep Models and Classifiers at the 37th International Conference on Machine Learning. Virtual, Jul 12-18, 2020. DOI
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models.
XXAI @ICML 2020 - Workshop on Extending Explainable AI Beyond Deep Models and Classifiers at the 37th International Conference on Machine Learning. Virtual, Jul 12-18, 2020. DOI
Related
31.07.2026
Benedikt Wiestler: We Want to Build a Time Machine
MCML PI Benedikt Wiestler explains how AI models help to develop specific strategies in clinical therapy for brain tumor patients.
28.07.2026
Gaps in the Benchmark: Why Medical AI Fails in the Real World
MCML researchers show in Nature Health how dynamic red teaming exposes hidden weaknesses in Medical AI beyond static benchmarks.
