Author

Karl Pierce

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Jul 2026

Accelerating the Canonical Polyadic Alternating Least Squares Optimization via a Randomized Interpolative Decomposition

This QR-based leverage score sampling method outperforms previously published schemes as it does not, in principle, require the resampling of the target tensor or recomputing the leverage scores of the KRP, minimizing the computational and storage overhead of the CPD-ALS procedure.

Israa Fakih, L. Grigori, Karl Pierce · arXiv.org · 1 citation

Preprint Aug 2026

Accelerated Learning of High Dimensional Functions with a Tensor-Featured Training Network

This work presents a method to accelerate the optimization of learning high dimensional functions using deep neural network (DNN), and studies the effect of adding features which distill pretrained DNN into TNs using a discretize and decompose strategy.

Karl Pierce, Y. Khoo, Haizhao Yang · 0 citations