4 papers
Bias Robustness of Genetic Multi-Criteria Sorting versus Learned Rankers under Proxy Skew and Label Contamination
Vladyslav Shevchuk, Carlos Uziel Pérez Malla, Philipp Wissgott
Learning-to-rank (LTR) models can align rankings with undesignated signals when those signals appear as features or leak into training labels. We compare label-free genetic multi-c…
Evolutionary Data Theory: On the Similarities between Data Problems and Evolutionary Games
Philipp Wissgott
Applying the concepts and formalism from Evolutionary Game Theory to the data regime, the fundamental paradigms of Evolutionary Data Theory are introduced. It is shown that essenti…
Feature weighting for data analysis via evolutionary simulation
Aris Daniilidis, Alberto Domínguez Corella, Philipp Wissgott
We analyze an algorithm for assigning weights prior to scalarization in discrete multi-objective problems arising from data analysis. The algorithm evolves weights (interpreted as…
Genetic AI: Evolutionary Games for ab initio dynamic Multi-Objective Optimization
Philipp Wissgott
We introduce Genetic AI, a novel method for multi-objective optimization without external parameters or predefined weights. The method can be applied to all problems that can be fo…