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Found 2 papers, 1 papers with code
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
Finally, we propose and analyze an estimator of the inverse covariance matrix of random regression coefficients based on data from the training tasks.
Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm
Statistical machine learning models trained with stochastic gradient algorithms are increasingly being deployed in critical scientific applications.
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