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Stochastic Constrained DRO with a Complexity Independent of Sample Size
Distributionally Robust Optimization (DRO), as a popular method to train robust models against distribution shift between training and test sets, has received tremendous attention in recent years.
Network Revenue Management with Demand Learning and Fair Resource-Consumption Balancing
We introduce the regularized revenue, i. e., the total revenue with a balancing regularization, as our objective to incorporate fair resource-consumption balancing into the revenue maximization goal.
Fairness-aware Online Price Discrimination with Nonparametric Demand Models
To handle this general class, we propose a soft fairness constraint and develop a dynamic pricing policy that achieves $\tilde{O}(T^{4/5})$ regret.
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