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Questions tagged [convex-optimization]

Convex minimization, a subfield of optimization, studies the problem of minimizing convex functions over convex sets. The convexity property can make optimization in some sense "easier" than the general case - for example, any local minimum must be a global minimum.

Applications:

  • automatic control systems
  • estimation and signal processing
  • communications and networks,
  • electronic circuit design
  • data analysis and modeling
  • statistics
  • finance
305 questions
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Armadillo join_cols() compile error

I'm trying my hand at doing some simple convex programming with Armadillo, but I might be getting lost in the syntax (or installation). I have the following: int M, N; // these are initialised to > 0 values. vec X; vec B = ones(M); // some…
lsdavies
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Matlab convex optimisation toolbox. Optimisation variable not shown

I'm using the convex optimisation toolbox in matlab and the objective function gets minimized and the value is shown. But the optimisation variable for which minima is achieved, I cannot find. Will someone tell me how to find it?
sprajagopal
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what does this notation mean ?

I was reading about k-strong convexity and came a across an equation like this f(x_1) >= f(x_2) + <\Delta f(x_2), x_1-x_2> + (k/2)*(||x_1-x_2||^2) Could some one explain what the notation <> means? Sorry for the errors with latex.
krishna
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which papers shows convexity in cost function and loss functions?

We know in the neural network if we want the global minimum, we need the loss function to be convex, so is there any paper shows that and talks about that?
A.omrani
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Specify solver in CVXR

I am new to the package CVXR. I am using it to do the convex optimization within each iteration of EM algorithms. Everything is fine at first but after 38 iterations, I have an error: Error in valuesById(object, results_dict, sym_data, solver) :…
TDo
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