A spectral decomposition approach for multi-view covariance estimation yields conjugate normal-inverse-gamma posteriors and high-dimensional asymptotic guarantees.
Inference on covariance structure in high- dimensional multi-view data
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Large empirical study of 56 optimizers on 1092 BBVI tasks finds no single winner but a selection of five suffices for near-best performance.
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Inference on covariance structure in high-dimensional multi-view data
A spectral decomposition approach for multi-view covariance estimation yields conjugate normal-inverse-gamma posteriors and high-dimensional asymptotic guarantees.
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Large-scale empirical tuning and comparison of default optimizers for variational inference
Large empirical study of 56 optimizers on 1092 BBVI tasks finds no single winner but a selection of five suffices for near-best performance.