Tag: least
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Fast and Exact Least Absolute Deviations Line Fitting via Piecewise Affine Lower-Bounding
Fast and Exact Least Absolute Deviations Line Fitting via Piecewise Affine Lower-Bounding arXiv:2512.20682v1 Announce Type: new Abstract: Least-absolute-deviations (LAD) line fitting is robust to outliers but computationally more involved than least squares regression. Although the literature includes linear and near-linear time algorithms for the LAD line fitting problem, these methods are difficult to implement and,…
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Hybrid least squares for learning functions from highly noisy data
Hybrid least squares for learning functions from highly noisy data arXiv:2507.02215v1 Announce Type: new Abstract: Motivated by the need for efficient estimation of conditional expectations, we consider a least-squares function approximation problem with heavily polluted data. Existing methods that are powerful in the small noise regime are suboptimal when large noise is present. We propose…
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Generalized Least Squares Kernelized Tensor Factorization
Generalized Least Squares Kernelized Tensor Factorization arXiv:2412.07041v1 Announce Type: new Abstract: Real-world datasets often contain missing or corrupted values. Completing multidimensional tensor-structured data with missing entries is essential for numerous applications. Smoothness-constrained low-rank factorization models have shown superior performance with reduced computational costs. While effective at capturing global and long-range correlations, these models struggle to…