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math.ST2021
Support Recovery with Stochastic Gates: Theory and Application for Linear Models
Soham Jana, Henry Li, Yutaro Yamada +1
Consider the problem of simultaneous estimation and support recovery of the coefficient vector in a linear data model with additive Gaussian noise. We study the problem of estimati…
math.ST2021
Refined Least Squares for Support Recovery
Ofir Lindenbaum, Stefan Steinerberger
We study the problem of exact support recovery based on noisy observations and present Refined Least Squares (RLS). Given a set of noisy measurement $$ \myvec{y} = \myvec{X}\myvecθ…
math.ST2020
Randomly Aggregated Least Squares for Support Recovery
Ofir Lindenbaum, Stefan Steinerberger
We study the problem of exact support recovery: given an (unknown) vector , we are given access to the noisy measurement where $X \in…