![[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 In this talk spanning about 36 minutes we discuss an issue which lies at the heart of modern convex I recommend you watch in 1.25x or 1.5x to not waste time. We derive a fundamental inequality and derive from it the statement that the distance to any solution is convergent and in ...
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