← 研踪 PaperTrailarXiv:2606.14627 · v2
Algebraic Operations on Tensor Trains
首次提交 2026-06-13 00:53
版本更新 2026-10-27 22:51
雷达观测 2026-10-29 00:34
摘要
The tensor train (TT) model is widely used to approximate high-dimensional tensors, enabling efficient handling of data that may exceed available memory. TT helps address the curse of dimensionality in applications such as system identification and dynamic programming. In some applications, TT is known as a ``matrix product state" (MPS). The last product is also known under the acronym MPO--MPS. The proposed algorithms achieve an improved trade-off between computational efficiency and accuracy compared to state-of-the-art methods.
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v2 · 2026-10-27 22:51 · 最新观测版本
Algebraic Operations on Tensor Trains
The tensor train (TT) model is widely used to approximate high-dimensional tensors, enabling efficient handling of data that may exceed available memory. TT helps address the curse of dimensionality in applications such as system identification and dynamic programming. In some applications, TT is known as a ``matrix product state" (MPS). The last product is also known under the acronym MPO--MPS. The proposed algorithms achieve an improved trade-off between computational efficiency and accuracy compared to state-of-the-art methods.
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