Subgradient Method

Hope you will enjoy this video. I know my voiceover is lacking some emotion but i will try my best to improve that for my next video.

We show two useful properties of the function values for the

I recommend you watch in 1.25x or 1.5x to not waste time.

We formulate the

Professor Boyd lectures on

... is why I keep writing

Definition of

Neither the lasso nor the SVM objective function is differentiable, and we had to do some work for each to optimize with ...

If you find our videos helpful you can support us by buying something from amazon. https://www.amazon.com/?tag=wiki-audio-20 ...

In this video, we dive deep into

Ryan Tibshirani @ Stats, CMU. http://www.stat.cmu.edu/~ryantibs/convexopt/

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department.

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department.

Professor Boyd covers

Professor Stephen Boyd, of the Stanford University Electrical Engineering department, gives the final lecture on convex ...

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department.

Lecture at NorthWestern University, April 2016. Slides at http://www.mit.edu/~dimitrib/Incremental_Survey_Slides_2016.pdf ...

F of X bar it is finite it's less than infinity okay an element V in R is current a

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department.

Ashia Wilson (MIT) https://simons.berkeley.edu/talks/tbd-332 Geometric