Neural Information Processing Systems· 2016
Supervised Learning with Tensor Networks
- 214citations
- 2016year
Short summary
Tensor networks, specifically matrix product states (tensor trains), can parameterize non-linear kernel learning models, achieving <1% test error on the MNIST dataset.
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Computational MathematicsMathematics