High dimensional linear regression using lattice basis reduction
© 2018 Curran Associates Inc.All rights reserved. We consider a high dimensional linear regression problem where the goal is to efficiently recover an unknown vector β∗ from n noisy linear observations Y = Xβ∗ + W ∈ Rn, for known X ∈ Rn×p and unknown W ∈ Rn. Unlike most of the literature on this mod...
| Format: | Article |
|---|---|
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/1721.1/137333 |