Adaptive hierarchical subtensor partitioning for tensor compression
SIAM Journal on Scientific Computing, 2021•SIAM
In this work a numerical method is proposed to compress a tensor by constructing a
piecewise tensor approximation. This is constructed by partitioning a tensor into subtensors
and by constructing a low-rank tensor approximation (in a given format) in each subtensor.
Neither the partition nor the ranks are fixed a priori, but, instead, they are obtained in order to
fulfill a prescribed accuracy and optimize the storage. Some numerical experiments are
proposed to illustrate the method.
piecewise tensor approximation. This is constructed by partitioning a tensor into subtensors
and by constructing a low-rank tensor approximation (in a given format) in each subtensor.
Neither the partition nor the ranks are fixed a priori, but, instead, they are obtained in order to
fulfill a prescribed accuracy and optimize the storage. Some numerical experiments are
proposed to illustrate the method.
In this work a numerical method is proposed to compress a tensor by constructing a piecewise tensor approximation. This is constructed by partitioning a tensor into subtensors and by constructing a low-rank tensor approximation (in a given format) in each subtensor. Neither the partition nor the ranks are fixed a priori, but, instead, they are obtained in order to fulfill a prescribed accuracy and optimize the storage. Some numerical experiments are proposed to illustrate the method.
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