4 papers
Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling
David Svensson, Erik Hermansson, Nikolaos Nikolaou +2
In recent years, two parallel research trends have emerged in machine learning, yet their intersections remain largely unexplored. On one hand, there has been a significant increas…
Inferring Causal Direction from Observational Data: A Complexity Approach
Nikolaos Nikolaou, Konstantinos Sechidis
At the heart of causal structure learning from observational data lies a deceivingly simple question: given two statistically dependent random variables, which one has a causal eff…
Multi-target regression via output space quantization
Eleftherios Spyromitros-Xioufis, Konstantinos Sechidis, Ioannis Vlahavas
Multi-target regression is concerned with the prediction of multiple continuous target variables using a shared set of predictors. Two key challenges in multi-target regression are…
Ranking Biomarkers Through Mutual Information
Konstantinos Sechidis, Emily Turner, Paul D. Metcalfe +2
We study information theoretic methods for ranking biomarkers. In clinical trials there are two, closely related, types of biomarkers: predictive and prognostic, and disentangling…