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Is speckle noise more challenging to mitigate than additive noise?
Reihaneh Malekian, Hao Xing, Arian Maleki
We study the problem of estimating a function in the presence of both speckle and additive noises, commonly referred to as the de-speckling problem. Although additive noise has bee…
A note on the minimax risk of sparse linear regression
Yilin Guo, Shubhangi Ghosh, Haolei Weng +1
Sparse linear regression is one of the classical and extensively studied problems in high-dimensional statistics and compressed sensing. Despite the substantial body of literature…
Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
Haolin Zou, Arnab Auddy, Kamiar Rahnama Rad +1
Despite a large and significant body of recent work focused on estimating the out-of-sample risk of regularized models in the high dimensional regime, a theoretical understanding o…