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10.09.2024

Teaser image to MCML at ECML-PKDD 2024

 

MCML at ECML-PKDD 2024

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024). Vilnius, Lithuania, September 09-13, 2024

We are happy to announce that MCML researchers are represented with 8 papers at ECML-PKDD 2024:

H. Baniecki, G. Casalicchio, B. Bischl and P. Biecek.
On the Robustness of Global Feature Effect Explanations.
DOI.
C. Damke and E. Hüllermeier.
CUQ-GNN: Committee-Based Graph Uncertainty Quantification Using Posterior Networks.
DOI.
R. Fischer, M. Wever, S. Buschjäger and T. Liebig.
MetaQuRe: Meta-learning from Model Quality and Resource Consumption.
DOI.
S. Gilhuber, A. Beer, Y. Ma and T. Seidl.
FALCUN: A Simple and Efficient Deep Active Learning Strategy.
DOI.
P. Jahn, C. M. M. Frey, A. Beer, C. Leiber and T. Seidl.
Data with Density-Based Clusters: A Generator for Systematic Evaluation of Clustering Algorithms.
DOI.
Y. Liu, E. Nie, S. Feng, Z. Hua, Z. Ding, D. Wang, Y. Zhang and H. Schütze.
A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation.
DOI. GitHub.
F. Stermann, I. Chalkidis, A. Vahidi, B. Bischl and M. Rezaei.
Attention-Driven Dropout: A Simple Method to Improve Self-supervised Contrastive Sentence Embeddings.
DOI.
A. Vahidi, L. Wimmer, H. A. Gündüz, B. Bischl, E. Hüllermeier and M. Rezaei.
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning.
DOI.

10.09.2024

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