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cs.LG2018
Benefits of over-parameterization with EM
Ji Xu, Daniel Hsu, Arian Maleki
Expectation Maximization (EM) is among the most popular algorithms for maximum likelihood estimation, but it is generally only guaranteed to find its stationary points of the log-l…
cs.LG2018★ 9 cited
Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems
Shuaiwen Wang, Wenda Zhou, Arian Maleki +2
Consider the following class of learning schemes: \begin{equation} \label{eq:main-problem1} \hat{\boldsymbolβ} := \underset{\boldsymbolβ \in \mathcal{C}}{\arg\min} \;\sum_{j=1}^n \…