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Is there a way to identify singular points in a spectrahedron without finding the entire set?

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#convex-optimization #numerical-optimization #positive-semidefinite #semidefinite-programming #spectrahedra
130
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Efficient algorithm for determining whether value of convex optimization program is below some value?

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#optimization #convex-analysis #convex-optimization #numerical-optimization
443
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How to solve this quadratic program using the penalty method?

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#optimization #convex-optimization #numerical-optimization #quadratic-programming
618
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Variational inference: Does the natural gradient follow geodesics locally?

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#differential-geometry #statistical-inference #calculus-of-variations #numerical-optimization #information-geometry
101
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Semi-infinite programming discretization theorem from the book ,,Theory, Methods, and Applications'

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#optimization #numerical-optimization
35
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Initial feasible solution for barrier method

Published on
#numerical-optimization
681
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Maximize constrained log-sum

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#optimization #convex-optimization #numerical-optimization
72
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Stopping criterion

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#optimization #numerical-optimization #newton-raphson #gradient-descent
134
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Convergence of complex sequence with gradient descent

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#complex-analysis #optimization #cauchy-sequences #numerical-optimization #karush-kuhn-tucker
192
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Prove that superlinear convergence of gradients implies superlinear convergence of sequence itself

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#real-analysis #linear-algebra #numerical-methods #nonlinear-optimization #numerical-optimization
384
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Max-min and min-max equivalence for the optimization problem

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#proof-verification #optimization #maxima-minima #numerical-optimization #karush-kuhn-tucker
156
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How to optimize a function with the following constraints by using gradient descent?

Published on
#optimization #numerical-optimization #gradient-descent #non-convex-optimization
105
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Generalizing the conjugate gradient like this works?

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#linear-algebra #optimization #numerical-methods #numerical-optimization
63
Views

A global optima: $\text{max}_{x} \frac{1}{2}\left\| X (a + b) \right\|_2^2 \ \text{s.t.} \ a^T X b \leq \delta; 0 < x \leq 1$,$X := {\rm Diag}(x)$

Published on
#numerical-optimization #non-convex-optimization
84
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Vector subderivatives and "simple algebra" which turn out not to be so simple

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#linear-algebra #derivatives #numerical-optimization

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