Ordinary Least Squares
PulseAugur coverage of Ordinary Least Squares — every cluster mentioning Ordinary Least Squares across labs, papers, and developer communities, ranked by signal.
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New Theory Unveils and Corrects Bias in Random Projections for ML
Researchers have developed a new theoretical framework to address statistical bias in random oblique projections, a common technique in machine learning and numerical linear algebra. The work highlights how standard sam…
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Bayesian methods outperform classical sparse regression in prediction and uncertainty
A new benchmark study evaluated six sparse regression methods, comparing classical approaches like Lasso with Bayesian techniques such as Horseshoe and Spike-and-Slab. The research found that Bayesian methods generally …
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SHIFT estimator improves robust double machine learning for heavy-tailed data
Researchers have developed SHIFT, a new robust estimator for Double Machine Learning (DML) pipelines designed to handle heavy-tailed data contamination. SHIFT combines cross-fit nuisance orthogonalization with a kernel-…
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Researchers propose new bootstrap methods for AI-generated labels in economics
A new paper from Timothy Christensen proposes a coupled-label bootstrap method to address biases in OLS estimators that arise when using AI/ML-generated labels as covariates in economic regressions. The research highlig…