Timeline for Proving Ridge Regression is strictly convex
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
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| Nov 8, 2020 at 20:41 | history | edited | Firebug | CC BY-SA 4.0 |
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| Nov 4, 2020 at 14:12 | history | edited | Firebug | CC BY-SA 4.0 |
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| Nov 4, 2020 at 12:24 | comment | added | Firebug | I modified the answer, taking care to eliminate the degenerate case instead of implying it @Cm7F7Bb | |
| Nov 4, 2020 at 12:23 | history | edited | Firebug | CC BY-SA 4.0 |
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| Nov 4, 2020 at 7:15 | comment | added | user20160 | The argument could be modified to take care of @Cm7F7Bb's point, by noting that the particular form of the augmentation guarantees linearly independent columns (as long as the ridge parameter is greater than zero). | |
| Nov 4, 2020 at 3:25 | comment | added | Cm7F7Bb | OLS is not necessarily strictly convex. OLS is strictly convex if and only if the columns of the design matrix are linearly independent. | |
| Nov 3, 2020 at 16:17 | history | answered | Firebug | CC BY-SA 4.0 |