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A survey of contextual optimization methods for decision-making under uncertainty
Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …
learning (ML) community in combining prediction algorithms and optimization techniques to …
A survey of contextual optimization methods for decision making under uncertainty
U Sadana, A Chenreddy, E Delage, A Forel… - ar** from features to ordering decisions. Most existing …
Predict-then-calibrate: A new perspective of robust contextual lp
Contextual optimization, also known as predict-then-optimize or prescriptive analytics,
considers an optimization problem with the presence of covariates (context or side …
considers an optimization problem with the presence of covariates (context or side …
Data-driven conditional robust optimization
In this paper, we study a novel approach for data-driven decision-making under uncertainty
in the presence of contextual information. Specifically, we solve this problem from a …
in the presence of contextual information. Specifically, we solve this problem from a …
Integrated conditional estimation-optimization
Many real-world optimization problems involve uncertain parameters with probability
distributions that can be estimated using contextual feature information. In contrast to the …
distributions that can be estimated using contextual feature information. In contrast to the …
[HTML][HTML] A bilevel framework for decision-making under uncertainty with contextual information
In this paper, we propose a novel approach for data-driven decision-making under
uncertainty in the presence of contextual information. Given a finite collection of …
uncertainty in the presence of contextual information. Given a finite collection of …
Fast rates for contextual linear optimization
Incorporating side observations in decision making can reduce uncertainty and boost
performance, but it also requires that we tackle a potentially complex predictive relationship …
performance, but it also requires that we tackle a potentially complex predictive relationship …
Data‐driven research in retail operations—A review
We review the operations research/management science literature on data‐driven methods
in retail operations. This line of work has grown rapidly in recent years, thanks to the …
in retail operations. This line of work has grown rapidly in recent years, thanks to the …