9 citations · 20 across the 8 of their papers we have counts for
8 papers
Inter-Temporal Price Constraints in Dynamic Pricing: Performance Guarantees Under Price Monotonicity and Promotion Fatigue
Weiyuan Li, Paat Rusmevichientong, Huseyin Topaloglu
We study dynamic pricing problems under inter-temporal price constraints. We have resources with limited capacities. At each time period, we decide which products to make available…
Revenue Management with Calendar-Aware and Dependent Demands: Asymptotically Tight Fluid Approximations
Weiyuan Li, Paat Rusmevichientong, Huseyin Topaloglu
When modeling the demand in revenue management systems, a natural approach is to focus on a canonical interval of time, such as a week, so that we forecast the demand over each wee…
Debiasing In-Sample Policy Performance for Small-Data, Large-Scale Optimization
Vishal Gupta, Michael Huang, Paat Rusmevichientong
Motivated by the poor performance of cross-validation in settings where data are scarce, we propose a novel estimator of the out-of-sample performance of a policy in data-driven op…
Future Evolution of COVID-19 Pandemic in North Carolina: Can We Flatten the Curve?
Omar El Housni, Mika Sumida, Paat Rusmevichientong +2
On June 24th, Governor Cooper announced that North Carolina will not be moving into Phase 3 of its reopening process at least until July 17th. Given the recent increases in daily p…
Can Testing Ease Social Distancing Measures? Future Evolution of COVID-19 in NYC
Omar El Housni, Mika Sumida, Paat Rusmevichientong +2
The "New York State on Pause" executive order came into effect on March 22 with the goal of ensuring adequate social distancing to alleviate the spread of COVID-19. Pause will rema…
Efficient Empirical Bayes prediction under check loss using Asymptotic Risk Estimates
Gourab Mukherjee, Lawrence D. Brown, Paat Rusmevichientong
We develop a novel Empirical Bayes methodology for prediction under check loss in high-dimensional Gaussian models. The check loss is a piecewise linear loss function having differ…
A Tractable POMDP for a Class of Sequencing Problems
Paat Rusmevichientong, Benjamin van Roy
We consider a partially observable Markov decision problem (POMDP) that models a class of sequencing problems. Although POMDPs are typically intractable, our formulation admits tra…
Linearly Parameterized Bandits
Paat Rusmevichientong, John N. Tsitsiklis
We consider bandit problems involving a large (possibly infinite) collection of arms, in which the expected reward of each arm is a linear function of an -dimensional random vec…