1.6k citations · 4.2k across the 71 of their papers we have counts for
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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★ 12 cited
Correcting the bias in least squares regression with volume-rescaled sampling
Michał Dereziński, Manfred K. Warmuth, Daniel Hsu
Consider linear regression where the examples are generated by an unknown distribution on . Without any assumptions on the noise, the linear least squares solution for…
cs.LG2018★ 42 cited
Leveraged volume sampling for linear regression
Michał Dereziński, Manfred K. Warmuth, Daniel Hsu
Suppose an design matrix in a linear regression problem is given, but the response for each point is hidden unless explicitly requested. The goal is to sample only a s…