Certifying Neural Network Robustness to Random Input Noisefrom Samples
The authors proposed a certification method to upper bound the propability of misclassification when the input noise follows an arbitrary probability distribution. The problem is formulated as a chance-contrained optimization problem which can be solved via scenario approach.
