14 citations · 135 across the 33 of their papers we have counts for
4 papers · 1 filter
The Knowledge Gradient with Logistic Belief Models for Binary Classification
Yingfei Wang, Chu Wang, Warren Powell
We consider sequential decision making problems for binary classification scenario in which the learner takes an active role in repeatedly selecting samples from the action pool an…
Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures
Daniel R. Jiang, Warren B. Powell
In this paper, we consider a finite-horizon Markov decision process (MDP) for which the objective at each stage is to minimize a quantile-based risk measure (QBRM) of the sequence…
Regularized Decomposition of High-Dimensional Multistage Stochastic Programs with Markov Uncertainty
Tsvetan Asamov, Warren B. Powell
We develop a quadratic regularization approach for the solution of high-dimensional multistage stochastic optimization problems characterized by a potentially large number of time…
The Knowledge Gradient Policy Using A Sparse Additive Belief Model
Yan Li, Han Liu, Warren Powell
We propose a sequential learning policy for noisy discrete global optimization and ranking and selection (R\&S) problems with high dimensional sparse belief functions, where there…