28.06.2024
MCML at COLT 2024
One Accepted Paper
37th Annual Conference on Learning Theory, Edmonton, Canada, Jun 30-Jul 03, 2024
We are happy to announce that MCML researchers have contributed a total of 1 paper to COLT 2024. Congrats to our researchers!
Main Track (1 paper)
C. M. Verdun • O. Melnyk • F. Krahmer • P. Jung
Fast, blind, and accurate: Tuning-free sparse regression with global linear convergence.
COLT 2024 - 37th Annual Conference on Learning Theory. Edmonton, Canada, Jun 30-Jul 03, 2024. URL
Fast, blind, and accurate: Tuning-free sparse regression with global linear convergence.
COLT 2024 - 37th Annual Conference on Learning Theory. Edmonton, Canada, Jun 30-Jul 03, 2024. URL
Related
10.06.2026
How Should Researchers Report Their Use of LLMs?
Is AI making science impossible to replicate? Stefan Feuerriegel and the MCML team introduce the GUIDE-LLM framework in Nature.
02.06.2026
Benjamin Lange: The Real Risk of AI Agents Is Manipulation Through Kindness
MCML Junior Research Group Leader Benjamin Lange examines how trust in AI agents can itself become a source of risk.
02.06.2026
MCML at CVPR 2026
MCML researchers are represented with 28 papers at CVPR 2026 (26 Main, and 2 Workshops).
