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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 enter image description here enter image description here.enter image description here

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 optimizationenter image description here.enter image description here

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 enter image description here enter image description here.enter image description here

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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 optimizationenter image description here.enter image description here