![Lecture 7 (part 2): Subgradient method [out of focus]](https://i.ytimg.com/vi/2Lftnn1w8FA/mqdefault.jpg)
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Okay so these are kind of two classic results on the Okay so that was the end of our I mean the trickiness with subgrading Ryan Tibshirani @ Stats, CMU. stat.cmu.edu/~ryantibs/convexopt/ I'm sorry for this video being out of focus. Please refer to the course website for slides and notes. Chapter 5: Convex Numerical algorithms 5.1: The Note: sound cuts out for last 20 minutes or so, sorry! Okay so i guess that'll end up that'll finish our I recommend you watch in 1.25x or 1.5x to not waste time. To So today we're going to talk about
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