Tag: boldsymbol
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Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws arXiv:2508.03688v1 Announce Type: new Abstract: We study the optimization and sample complexity of gradient-based training of a two-layer neural network with quadratic activation function in the high-dimensional regime, where the data is generated as $y propto sum_{j=1}^{r}lambda_j sigmaleft(langle boldsymbol{theta_j}, boldsymbol{x}rangleright), boldsymbol{x} sim N(0,boldsymbol{I}_d)$,…
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Inequalities for Optimization of Classification Algorithms: A Perspective Motivated by Diagnostic Testing
Inequalities for Optimization of Classification Algorithms: A Perspective Motivated by Diagnostic Testing arXiv:2508.01065v1 Announce Type: new Abstract: Motivated by canonical problems in medical diagnostics, we propose and study properties of an objective function that uniformly bounds uncertainties in quantities of interest extracted from classifiers and related data analysis tools. We begin by adopting a set-theoretic…
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Fast Debiasing of the LASSO Estimator
Fast Debiasing of the LASSO Estimator arXiv:2502.19825v1 Announce Type: new Abstract: In high-dimensional sparse regression, the textsc{Lasso} estimator offers excellent theoretical guarantees but is well-known to produce biased estimates. To address this, cite{Javanmard2014} introduced a method to “debias” the textsc{Lasso} estimates for a random sub-Gaussian sensing matrix $boldsymbol{A}$. Their approach relies on computing an “approximate…