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Name: Chiara Balestra
Type: User
Company: TU Dortmund
Bio: Ph.D. Student, Master in Pure Mathematics
Name: Chiara Balestra
Type: User
Company: TU Dortmund
Bio: Ph.D. Student, Master in Pure Mathematics
FairMC is a fair rank aggregation approach based on Markov Chains. By modifying the transition matrix and enforcing fairness in the transition probabilities across the protected and unprotected groups, fairMC guarantees fairness in the representation of the items at the consensus ranking level.
Reference implementation of the paper Redundancy-aware unsupervised ranking based on game theory - application to gene enrichment analysis
Reference implementation of the paper Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data
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