tensor network
Many-body Approximation for Non-negative Tensors
We present an alternative approach to decompose non-negative tensors, called many-body approximation .
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Y otam Alexander *, Nimrod De La Vega
The question of what makes a data distribution suitable for deep learning is a fundamental open problem.
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Expressive power of tensor-network factorizations for probabilistic modeling
Ivan Glasser, Ryan Sweke, Nicola Pancotti, Jens Eisert, Ignacio Cirac
Whenusedtomodelprobability distributions, theyexhibit tractable likelihoods and admit efficient learning algorithms.
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Cost
We then provide an algorithm to efficiently sketch input data using such embeddings. The sketch size of the embedding used in the algorithm has a linear dependence on the number of sketching dimensions of the input.
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