Linear regression with partially mismatched data: local search with theoretical guarantees
Abstract Linear regression is a fundamental modeling tool in statistics and related fields. In this paper, we study an important variant of linear regression in which the predictor-response pairs are partially mismatched. We use an optimization formulation to simultaneously learn the...
Main Authors: | Mazumder, Rahul, Wang, Haoyue |
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Other Authors: | Sloan School of Management |
Format: | Article |
Language: | English |
Published: |
Springer Berlin Heidelberg
2022
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Online Access: | https://hdl.handle.net/1721.1/144400 |
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