Conceptually, I don't understand what least angle regression Least Angle Regression (LARS) is and why it solves LASSO (pdf).
We know that LASSO is:
$$\arg \min_x {\left\| A x - y \right\|}_{2}^{2} + \lambda {\left\| x \right\|}_{1}$$
From my understanding LARS is exactly like line search from CGD, where you take the variable that gives you the most desire result and iterate through.
Can someone give a walk through on how LARS solves LASSO?