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New Bidirectional Random Projections Method Analyzed for OLS Regression

By PulseAugur Editorial · [1 sources] ·

This paper introduces bidirectional random projections as a method for Ordinary Least Squares (OLS) regression in a fixed design setting. The research develops an expected excess loss bound for OLS estimators constructed using these projections, comparing it to existing bounds. The findings suggest a potential gap in performance that scales with the dimensionality of the projected data and the ratio of sample sizes, with numerical results on real-world data supporting these implications. AI

IMPACT Introduces a novel statistical technique for regression analysis, potentially impacting machine learning model development.

RANK_REASON The cluster contains an academic paper detailing a new statistical method. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Chao Lan, Luyuan Yang ·

    Bidirectional Random Projections

    arXiv:2606.10377v1 Announce Type: cross Abstract: This paper analyzes bidirectional random projections for ordinary least squares (OLS) regression under the fixed design setting. Let $(X,Y) \in \mathbb{R}^{n \times p} \times \mathbb{R}^n$ be a sample and $R \in \mathbb{R}^{n_1 \t…

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