2 citations · 2 across the 15 of their papers we have counts for
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stat.ML2026
Fairness in multi-class multi-group classification problems via contextial coherent risk measures
Darinka Dentcheva, Xiangyu Tian
We propose a new design of fair classifiers for multi-class classification problems in the presence of vector-valued sensitive attributes. In that scenario each sensitive attribute…
stat.ML2025
Risk-averse Fair Multi-class Classification
Darinka Dentcheva, Xiangyu Tian
We develop a new classification framework based on the theory of coherent risk measures and systemic risk. The proposed approach is suitable for multi-class problems when the data…
stat.ML2018
Risk-Averse Classification
Constantine Vitt, Darinka Dentcheva, Hui Xiong
We develop a new approach to solving classification problems, which is bases on the theory of coherent measures of risk and risk sharing ideas. The proposed approach aims at design…