Bound Tightening Using Rolling-Horizon Decomposition for Neural Network Verification.
Haoruo ZhaoHassan L. HijaziHaydn JonesJuston MooreMathieu TanneauPascal Van HentenryckPublished in: CPAIOR (2) (2024)
Keyphrases
- rolling horizon
- neural network
- lot sizing
- single machine
- lower bound
- upper bound
- back propagation
- neural network model
- model checking
- decomposition method
- artificial neural networks
- self organizing maps
- error bounds
- pattern recognition
- neural network is trained
- recurrent neural networks
- wavelet packet
- fuzzy neural network
- associative memory
- data sets
- multilayer perceptron
- worst case
- reinforcement learning
- prediction model
- training algorithm
- network architecture
- multistage
- feedforward neural networks
- signature verification
- decomposition algorithm
- asynchronous circuits
- fuzzy artmap
- verification method
- genetic algorithm
- functional verification