An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression

NeurIPS 2018 Sheng ChenArindam Banerjee

Multi-response linear models aggregate a set of vanilla linear models by assuming correlated noise across them, which has an unknown covariance structure. To find the coefficient vector, estimators with a joint approximation of the noise covariance are often preferred than the simple linear regression in view of their superior empirical performance, which can be generally solved by alternating-minimization type procedures... (read more)

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