5.3 Prox Gradient -- Rates of Convergence

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  1. Constantine Caramanis
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Комментарии
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At 5:07 it's actually gradient of g(x)

rodasyt
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Sir, why are we calling the convergence rate for smooth and strongly convex case "Linear"?

sandippaul
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Thank you so much for these lectures. A quick question: when upper bounding (a) term using \beta-smoothness (timestamp: 4:40), we assume beta <= eta, right? But in the previous video when you introduced this key lemma, you mentioned that eta <= 1/beta, but I think proof goes through by assuming beta <= eta instead. Am I missing something?

lylekim