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2020 – today
- 2024
[b1]Chiara Balestra:
Rankings and importance scores as multi-facets of explainable machine learning. Dortmund University, Germany, 2024- [c4]Chiara Balestra, Antonio Ferrara, Emmanuel Müller:
FairMC Fair-Markov Chain Rank Aggregation Methods. DaWaK 2024: 315-321 - [c3]Simon Klüttermann
, Chiara Balestra, Emmanuel Müller:
On the Efficient Explanation of Outlier Detection Ensembles Through Shapley Values. PAKDD (3) 2024: 43-55 - [i5]Chiara Balestra, Andreas Mayr, Emmanuel Müller:
Ranking evaluation metrics from a group-theoretic perspective. CoRR abs/2408.16009 (2024) - 2023
- [c2]Chiara Balestra, Bin Li, Emmanuel Müller:
slidSHAPs - sliding Shapley Values for correlation-based change detection in time series. DSAA 2023: 1-10 - [i4]Chiara Balestra, Carlo Maj, Emmanuel Müller, Andreas Mayr:
Redundancy-aware unsupervised rankings for collections of gene sets. CoRR abs/2307.16182 (2023) - [i3]Chiara Balestra, Bin Li, Emmanuel Müller:
On the Consistency and Robustness of Saliency Explanations for Time Series Classification. CoRR abs/2309.01457 (2023) - 2022
- [c1]Chiara Balestra, Florian Huber, Andreas Mayr, Emmanuel Müller:
Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data. DaWaK 2022: 97-111 - [i2]Chiara Balestra, Florian Huber, Andreas Mayr, Emmanuel Müller:
Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data. CoRR abs/2205.09060 (2022) - [i1]Chiara Balestra, Carlo Maj, Emmanuel Müller, Andreas Mayr:
Redundancy-aware unsupervised ranking based on game theory - application to gene enrichment analysis. CoRR abs/2207.12184 (2022)
Coauthor Index
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