A Theory of the Risk for Optimization with Relaxation and its Application to Support Vector Machines.
Marco C. CampiSimone GarattiPublished in: J. Mach. Learn. Res. (2021)
Keyphrases
- support vector
- learning machines
- large margin classifiers
- optimization algorithm
- high risk
- global optimization
- optimization process
- portfolio theory
- structural risk minimization
- logistic regression
- optimization problems
- classification accuracy
- hyperplane
- risk assessment
- decision function
- kernel machines
- convex relaxation
- svm classifier
- risk factors
- constrained optimization
- feature selection
- risk management
- kernel methods
- optimization method
- theoretical framework
- decision making
- probabilistic relaxation
- stochastic programming
- robust optimization
- training examples
- computational model
- decision theory