Subgradients

Summary

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. I recommend you watch in 1.25x or 1.5x to not waste time. In today's lecture I'm going to talk about So we can define subgrading descent before we just replace the gradient by Neither the lasso nor the SVM objective function is differentiable, and we had to do some work for each to optimize with ... This video is part of a full series on Parametric Regression in Machine Learning. Start from the beginning here: ... So, in technical language you will say that g 1 and g 2 are the Pierre Schaus legt uit hoe subgradiënt-algoritmen worden toegepast op constrained shortest path-problemen. Hierbij wordt ingegaan op het bijwerken van Lagrange-multiplicatoren en het beheren van haalbare versus niet-haalbare oplossingen tijdens het iteratieve optimalisatieproces. Okay so all we already covered all this and this is the jumping-off point just to give some Ever wondered how machine learning models optimize when their loss functions aren't perfectly smooth? This video dives deep ...