Ho-Nguyen Nam

Overcoming Demand Censoring through Randomization for Risk-Sensitive Newsvendor Learning

We study online newsvendor learning with bounded demand, censored observations, and convex nonlinear shortage costs. Because stockouts can conceal the shortage magnitudes needed by gradient-based algorithms, we use randomized ordering to construct unbiased subgradient estimates. We characterize admissible randomization...