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Found 7 papers, 5 papers with code
Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective
In this paper, we show that a reverse behavior appears when the model class is well-specified and there is sufficient data.
Balanced Off-Policy Evaluation for Personalized Pricing
We consider a personalized pricing problem in which we have data consisting of feature information, historical pricing decisions, and binary realized demand.
Decision Trees for Decision-Making under the Predict-then-Optimize Framework
We consider the use of decision trees for decision-making problems under the predict-then-optimize framework.
Market Segmentation Trees
We seek to provide an interpretable framework for segmenting users in a population for personalized decision-making.
Applications
Generalization Bounds in the Predict-then-Optimize Framework
A natural loss function in this environment is to consider the cost of the decisions induced by the predicted parameters, in contrast to the prediction error of the parameters.
Smart "Predict, then Optimize"
Our SPO+ loss function can tractably handle any polyhedral, convex, or even mixed-integer optimization problem with a linear objective.
A Practical Method for Solving Contextual Bandit Problems Using Decision Trees
We propose a new method for the contextual bandit problem that is simple, practical, and can be applied with little or no domain expertise.
