93 citations · 177 across the 6 of their papers we have counts for
6 papers
Conditional Approximate Normalizing Flows for Joint Multi-Step Probabilistic Forecasting with Application to Electricity Demand
Arec Jamgochian, Di Wu, Kunal Menda +2
Some real-world decision-making problems require making probabilistic forecasts over multiple steps at once. However, methods for probabilistic forecasting may fail to capture corr…
Bid Optimization by Multivariable Control in Display Advertising
Xun Yang, Yasong Li, Hao Wang +4
Real-Time Bidding (RTB) is an important paradigm in display advertising, where advertisers utilize extended information and algorithms served by Demand Side Platforms (DSPs) to imp…
Analyzing and provably improving fixed budget ranking and selection algorithms
Di Wu, Enlu Zhou
This paper studies the fixed budget formulation of the Ranking and Selection (R&S) problem with independent normal samples, where the goal is to investigate different algorithms' c…
Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising
Di Wu, Xiujun Chen, Xun Yang +5
Real-time bidding (RTB) is an important mechanism in online display advertising, where a proper bid for each page view plays an essential role for good marketing results. Budget co…
Data-driven Ranking and Selection under Input Uncertainty
Di Wu, Yuhao Wang, Enlu Zhou
We consider a simulation-based Ranking and Selection (R&S) problem with input uncertainty, where unknown input distributions can be estimated using input data arriving in batches o…
A Bayesian Risk Approach to Data-driven Stochastic Optimization: Formulations and Asymptotics
Di Wu, Helin Zhu, Enlu Zhou
A large class of stochastic programs involve optimizing an expectation taken with respect to an underlying distribution that is unknown in practice. One popular approach to address…