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PRODID:-//pretalx//pretalx.com//juliacon-2022//talk//Z9Y73V
BEGIN:VEVENT
UID:pretalx-juliacon-2022-Z9Y73V@pretalx.com
DTSTART:20220728T133000Z
DTEND:20220728T134000Z
DESCRIPTION:Most (Mathematical) Optimization problems are subject to bounds
  on the decision variables. In general\, a nonlinear cost function `f(x)` 
 is to be minimized\, with the vector `x` constrained by simple bounds `l <
 = x <= u`. The *Projected Gradient* class of methods is tailored for this 
 very optimization problem. Our package includes various Projected Gradient
  methods\, fully implemented in Julia. We make use of Julia's Iterator int
 erface\, allowing for user-defined termination criteria.
DTSTAMP:20260515T074002Z
LOCATION:Blue
SUMMARY:Progradio.jl - Projected Gradient Optimization - Eduardo M. G. Vila
URL:https://pretalx.com/juliacon-2022/talk/Z9Y73V/
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