A robust optimization approach to kernel-based nonparametric error-in-variables identification in the presence of bounded noise.
Vito CeroneEdoardo FaddaDiego RegrutoPublished in: ACC (2017)
Keyphrases
- robust optimization
- chance constrained
- classification noise
- mathematical programming
- portfolio optimization
- stochastic programming
- risk measures
- decision theory
- artificial intelligence
- variable selection
- missing data
- kernel methods
- genetic algorithm
- input variables
- semidefinite programming
- high dimensional
- bayesian networks