link to ex04 on home

README.md

@@ -36,7 +36,7 @@ Non-Convex Optimization: Convergence to Critical Points, Alternating minimizatio
 | #1  | 25.2. | Introduction, Convexity                               | [notes](../../raw/master/lecture_notes/lecture-notes.pdf), [slides](../../raw/master/slides/lecture01.pdf) | [lab01](../../tree/master/labs/ex01/) |
 | #2  | 4.3.  | Gradient Descent                                      | [notes](../../raw/master/lecture_notes/lecture-notes.pdf), [slides](../../raw/master/slides/lecture02.pdf) | [lab02](../../tree/master/labs/ex02/) |
 | #3  | 11.3. | Projected Gradient Descent                            | [notes](../../raw/master/lecture_notes/lecture-notes.pdf), [slides](../../raw/master/slides/lecture03.pdf) | [lab03](../../tree/master/labs/ex03/) |
-| #4  | 18.3. | Proximal and Subgradient Descent                      | [notes](../../raw/master/lecture_notes/lecture-notes.pdf),                                                 |                                       |
+| #4  | 18.3. | Proximal and Subgradient Descent                      | [notes](../../raw/master/lecture_notes/lecture-notes.pdf),                                                 | [lab04](../../tree/master/labs/ex04/)                                     |
 | #5  | 25.3. | Stochastic Gradient Descent, Non-Convex Optimization  | [notes](../../raw/master/lecture_notes/lecture-notes.pdf),                                                 |                                       |
 | #6  | 1.4.  | Non-Convex Optimization, Accelerated Gradient Descent | [notes](../../raw/master/lecture_notes/lecture-notes.pdf),                                                 |                                       |
 | #7  | 8.4.  | Newton's Method & Quasi-Newton                        | [notes](../../raw/master/lecture_notes/lecture-notes.pdf),                                                 |                                       |