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It is given in the book Machine Learning A probabilistic Perspective, but i am not able to understand it. Can some one provide an explanation for that ?

I am not clear with the way sub gradient is defined and how is it helping in the optimization .

It is given in the book Machine Learning A probabilistic Perspective, but i am not able to understand it. Can some one provide an explanation for that ?

I am not clear with the way sub gradient is defined and how is it helping in the optimization.

It is given in the book Machine Learning A probabilistic Perspective, but i am not able to understand it. Can some one provide an explanation for that ?

I am not clear with the way sub gradient is defined and how is it helping in the optimization .

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# What is the mathematical rigorous proof that L1 regularization will give sparse solution?

It is given in the book Machine Learning A probabilistic Perspective, but i am not able to understand it. Can some one provide an explanation for that ?

I am not clear with the way sub gradient is defined and how is it helping in the optimization.