![[CS292F 2020 Spring] Convex Optimization: Lecture 6 Subgradient Method and Proximal Gradient Descent](https://i.ytimg.com/vi/rNcNiTVDeG8/mqdefault.jpg)
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Note: sound cuts out for last 20 minutes or so, sorry! ... downsides requires that F be differentiable next Okay so that this rest of today's Ryan Tibshirani @ Stats, CMU. stat.cmu.edu/~ryantibs/convexopt/ Okay so that was the end of our I recommend you watch in 1.25x or 1.5x to not waste time. In this talk spanning about 36 minutes we discuss an issue which lies at the heart of modern convex Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his
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