02.08.2024
MCML at IJCAI 2024
Three Accepted Papers (2 Main, and 1 Workshop)
33rd International Joint Conference on Artificial Intelligence, Jeju, Korea, Aug 03-09, 2024
We are happy to announce that MCML researchers have contributed a total of 3 papers to IJCAI 2024: 2 Main, and 1 Workshop papers. Congrats to our researchers!
Main Track (2 papers)
J. Brandt • M. Wever • V. Bengs • E. Hüllermeier
Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO.
IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. DOI
Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO.
IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. DOI
J. G. Wiese • L. Wimmer • T. Papamarkou • B. Bischl • S. Günnemann • D. Rügamer
Towards Efficient Posterior Sampling in Deep Neural Networks via Symmetry Removal (Extended Abstract).
IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. DOI
Towards Efficient Posterior Sampling in Deep Neural Networks via Symmetry Removal (Extended Abstract).
IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. DOI
Workshops (1 paper)
P. Wicke • L. Hirlimann • J. M. Cunha
Using Analogical Reasoning to Prompt LLMs for their Intuitions of Abstract Spatial Schemas.
Analogy-ANGLE 2024 @IJCAI 2024 - 1st Workshop on Analogical Abstraction in Cognition, Perception, and Languageat the 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. PDF
Using Analogical Reasoning to Prompt LLMs for their Intuitions of Abstract Spatial Schemas.
Analogy-ANGLE 2024 @IJCAI 2024 - 1st Workshop on Analogical Abstraction in Cognition, Perception, and Languageat the 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. PDF
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16.09.2026
Vincent Fortuin Receives ERC Starting Grant for Reliable Small-Data AI
MCML PI Vincent Fortuin receives an ERC Starting Grant for AutoBayes, advancing reliable AI methods for learning from small datasets.
