Improved batch-means rates for SGD covariance estimation plus a minimax-optimal trajectory-regression estimator achieving Θ(n^{-(1-α)/2}) for Hessian-free inference.
arXiv preprint arXiv:2212.01259 , year=
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Develops a batch-free online covariance estimator for sketched Newton methods, proves its consistency, and demonstrates use for online statistical inference on regression and CUTEst problems.
A novel bias-reduced online covariance estimator for SGD achieves convergence rate n to the power (α-1)/2 times square root of log n without second-order derivatives.
citing papers explorer
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Online Covariance Estimation in Averaged SGD: Improved Batch-Mean Rates and Minimax Optimality via Trajectory Regression
Improved batch-means rates for SGD covariance estimation plus a minimax-optimal trajectory-regression estimator achieving Θ(n^{-(1-α)/2}) for Hessian-free inference.
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Online Covariance Matrix Estimation in Sketched Newton Methods
Develops a batch-free online covariance estimator for sketched Newton methods, proves its consistency, and demonstrates use for online statistical inference on regression and CUTEst problems.
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Refining Covariance Matrix Estimation in Stochastic Gradient Descent Through Bias Reduction
A novel bias-reduced online covariance estimator for SGD achieves convergence rate n to the power (α-1)/2 times square root of log n without second-order derivatives.