Neural Models for Output-Space Invariance in Combinatorial Problems.
Yatin NandwaniVidit Jain MausamParag SinglaPublished in: ICLR (2022)
Keyphrases
- combinatorial problems
- neural models
- output space
- input space
- constraint programming
- constraint satisfaction problems
- bio inspired
- metaheuristic
- combinatorial optimization
- constraint satisfaction
- neural network model
- traveling salesman problem
- neural model
- phase transition
- neural network
- structured output
- high dimensional
- artificial neural networks
- representative set
- spiking neural networks
- branch and bound algorithm
- global constraints
- training set
- recurrent neural networks
- user defined
- np hard
- high dimensional data
- biologically inspired
- feature space
- learning algorithm
- training process
- np complete
- low dimensional
- optimization problems
- dimensionality reduction
- evolutionary algorithm