17.02.2024

Teaser image to MCML at AAAI 2024

MCML at AAAI 2024

The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024). Vancouver, Canada, February 20-27, 2024

We are happy to announce that MCML researchers are represented with the following papers at AAAI 2024:


H. Chen, Y. Zhang, D. Krompass, J. Gu and V. Tresp.

FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning.
arXiv

P. Kolpaczki, V. Bengs, M. Muschalik and E. Hüllermeier.

Approximating the Shapley Value without Marginal Contributions.
arXiv

T. Ladner and M. Althoff.

Exponent Relaxation of Polynomial Zonotopes and Its Applications in Formal Neural Network Verification.

J. Lienen and E. Hüllermeier.

Mitigating Label Noise through Data Ambiguation.
arXiv

M. Muschalik and F. Fumagalli and B. Hammer and E. Hüllermeier.

Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.
arXiv

T. N. Wolf, F. Bongratz, A.-M. Rickmann, S. Pölsterl and C. Wachinger.

Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning.
arXiv

17.02.2024


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