A new perspective on boosting in linear regression via subgradient optimization and relatives
We analyze boosting algorithms [Ann. Statist. 29 (2001) 1189-1232; Ann. Statist. 28 (2000) 337-407; Ann. Statist. 32 (2004) 407-499] in linear regression from a new perspective: that of modern first-order methods in convex optimiz ation. We show that classic boosting algorithms in linear regression,...
| Main Authors: | , , , , |
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| Other Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Mathematical Statistics,
2018-05-10T18:57:26Z.
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| Subjects: | |
| Online Access: | Get fulltext |