Author

Jing-Chun Shao

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Preprint Sep 2026

Compressed Sensing with Quantized Tensor Trains (QTTs)

The storage and recovery of a vector of length \(2^d\) can become prohibitively expensive as \(d\) grows, a manifestation of the curse of dimensionality. For certain structured functions and multiscale quantities, the resulting discretized vectors admit compact quantized tensor train (QTT) representations after binary...

Jing-Chun Shao · 0 citations

Review Sep 2026

Worst-Case Completion of Tensors with Approximately Few ANOVA Terms

In this article, the problem of completing a tensor from some incomplete knowledge of its entries is treated by adopting a worst-case perspective, given the realistic assumption that the tensor's low-order ANOVA terms are dominant. We survey and leverage some recent all-purpose results from the field of Optimal Recover...

Simon Foucart, Jing-Chun Shao · 0 citations