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Optimization with convex constraints and convex objectives; notions related to convex optimization such as sub-gradients, normal cones, separating hyperplanes
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Optimization over sliding windows
Assume an objective function $f = g (X_{t_1},Y_{t_1}) + g (X_{t_2},Y_{t_2}) + g (X_{t_3},Y_{t_3}) + \dots+g (X_{t_n},Y_{t_n})$ where $g$ is a convex function. $X_{t_i}$ and $Y_{t_i}$ are sets of real …
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Coordinate descent conditions
The following is quoted from "Bertsekas, D. P. (1999). Nonlinear programming (p. 794). Belmont: Athena scientific".
Convergence of Coordinate Descent: Suppose a function $f$ is continuously differ …
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Block coordinate descent convergence rate
I have read some literature about the convergence rate of block coordinate descent. They all assume that the object function $f$ is Lipschitz continuous, is there any results for the convergence rate …