Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Tensor networks are approximations of high-order tensors which are efficient to work with and have been very successful for physics and mathematics applications.  demonstrate how algorithms for optimizing tensor networks can be adapted to supervised learning tasks by using matrix product states (tensor trains) to parameterize non-linear kernel learning models. For the MNIST data set  obtain less than 1% test set classification error.  discuss an interpretation of the additional structure imparted by the tensor network to the learned model.
['E. M. Stoudenmire', 'David J. Schwab']
I am writing a research paper on a idea Supervised Learning with Tensor Networks
[{"from": "human", "value": "I am writing a research paper on a idea Supervised Learning with Tensor Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Tensor networks are approximations of high-order tensors which are efficient to work with and have been very successful for physics and mathematics applications.  demonstrate how algorithms for optimizing tensor networks can be adapted to supervised learning tasks by using matrix product states (tensor trains) to parameterize non-linear kernel learning models. For the MNIST data set  obtain less than 1% test set classification error.  discuss an interpretation of the additional structure imparted by the tensor network to the learned model."}]