Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning.
Daniel KuhnPeyman Mohajerin EsfahaniViet Anh NguyenSoroosh Shafieezadeh-AbadehPublished in: CoRR (2019)
Keyphrases
- robust optimization
- machine learning
- chance constrained
- stochastic programming
- decision theory
- mathematical programming
- portfolio optimization
- lot sizing
- artificial intelligence
- risk measures
- theoretical framework
- active learning
- data mining
- multistage
- model selection
- support vector machine
- semidefinite programming
- probability distribution
- special case
- reinforcement learning
- learning algorithm
- chance constraints
- linear combination
- scheduling problem
- expected utility