Identity for multiple variables minimization Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)sufficient condition for KKT problemsKKT multipliers sign conventionSum greater than 1; minimization for non-strict inequalitiesSolve the closed form solution for argmax of $ x^Ty - x^Tln(x)$Complementary slackness in Hilbert spacesDoubt when applying Complementary Slackness TheoremIs it sufficient to prove Jensen's Inequality holds for an example probability distribution to prove that a function is convex?Understanding binding constraints associated with points in $mathbbR^3$Lagrange Mutiplier for inequality constraintInequality of $min$ and $max$ of functions and their convex-conjugates
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Identity for multiple variables minimization
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)sufficient condition for KKT problemsKKT multipliers sign conventionSum greater than 1; minimization for non-strict inequalitiesSolve the closed form solution for argmax of $ x^Ty - x^Tln(x)$Complementary slackness in Hilbert spacesDoubt when applying Complementary Slackness TheoremIs it sufficient to prove Jensen's Inequality holds for an example probability distribution to prove that a function is convex?Understanding binding constraints associated with points in $mathbbR^3$Lagrange Mutiplier for inequality constraintInequality of $min$ and $max$ of functions and their convex-conjugates
$begingroup$
I would like the prove the following identity:
$$minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]=minlimits_mathbfx[f(mathbfx)]+minlimits_mathbfy[g(mathbfy)]$$
At first, I supposed that this should be an inequality, because I tried proving this by doing:
beginalign
minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]geq minlimits_mathbfx,mathbfy[f(mathbfx)]+minlimits_mathbfx,mathbfy[g(mathbfy)]
endalign
But I am not sure if this is correct...
Could someone help me proving this by using some basic principles and properties? Also, are there any conditions/constraints over the functions so that the proposed equality holds?
inequality optimization maxima-minima
$endgroup$
add a comment |
$begingroup$
I would like the prove the following identity:
$$minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]=minlimits_mathbfx[f(mathbfx)]+minlimits_mathbfy[g(mathbfy)]$$
At first, I supposed that this should be an inequality, because I tried proving this by doing:
beginalign
minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]geq minlimits_mathbfx,mathbfy[f(mathbfx)]+minlimits_mathbfx,mathbfy[g(mathbfy)]
endalign
But I am not sure if this is correct...
Could someone help me proving this by using some basic principles and properties? Also, are there any conditions/constraints over the functions so that the proposed equality holds?
inequality optimization maxima-minima
$endgroup$
add a comment |
$begingroup$
I would like the prove the following identity:
$$minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]=minlimits_mathbfx[f(mathbfx)]+minlimits_mathbfy[g(mathbfy)]$$
At first, I supposed that this should be an inequality, because I tried proving this by doing:
beginalign
minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]geq minlimits_mathbfx,mathbfy[f(mathbfx)]+minlimits_mathbfx,mathbfy[g(mathbfy)]
endalign
But I am not sure if this is correct...
Could someone help me proving this by using some basic principles and properties? Also, are there any conditions/constraints over the functions so that the proposed equality holds?
inequality optimization maxima-minima
$endgroup$
I would like the prove the following identity:
$$minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]=minlimits_mathbfx[f(mathbfx)]+minlimits_mathbfy[g(mathbfy)]$$
At first, I supposed that this should be an inequality, because I tried proving this by doing:
beginalign
minlimits_mathbfx,mathbfy[f(mathbfx)+g(mathbfy)]geq minlimits_mathbfx,mathbfy[f(mathbfx)]+minlimits_mathbfx,mathbfy[g(mathbfy)]
endalign
But I am not sure if this is correct...
Could someone help me proving this by using some basic principles and properties? Also, are there any conditions/constraints over the functions so that the proposed equality holds?
inequality optimization maxima-minima
inequality optimization maxima-minima
edited Apr 1 at 15:01
bertozzijr
asked Apr 1 at 14:39
bertozzijrbertozzijr
6331720
6331720
add a comment |
add a comment |
1 Answer
1
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$begingroup$
You have
$$min_x,y (f(x)+g(y)) leq f(x)+g(y), quad textfor all,, x,y$$
which implies
$$min_x,y (f(x)+g(y)) leq min_x f(x)+ min_y g(y)$$
On the other hand
$$f(x)+g(y) geq min_x f(x) + min_y g(y), quad textfor all,, x,y$$
therefore
$$min_x,y (f(x)+g(y)) geq min_x f(x)+ min_y g(y)$$
So you have the equality.
$endgroup$
add a comment |
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1 Answer
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1 Answer
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active
oldest
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$begingroup$
You have
$$min_x,y (f(x)+g(y)) leq f(x)+g(y), quad textfor all,, x,y$$
which implies
$$min_x,y (f(x)+g(y)) leq min_x f(x)+ min_y g(y)$$
On the other hand
$$f(x)+g(y) geq min_x f(x) + min_y g(y), quad textfor all,, x,y$$
therefore
$$min_x,y (f(x)+g(y)) geq min_x f(x)+ min_y g(y)$$
So you have the equality.
$endgroup$
add a comment |
$begingroup$
You have
$$min_x,y (f(x)+g(y)) leq f(x)+g(y), quad textfor all,, x,y$$
which implies
$$min_x,y (f(x)+g(y)) leq min_x f(x)+ min_y g(y)$$
On the other hand
$$f(x)+g(y) geq min_x f(x) + min_y g(y), quad textfor all,, x,y$$
therefore
$$min_x,y (f(x)+g(y)) geq min_x f(x)+ min_y g(y)$$
So you have the equality.
$endgroup$
add a comment |
$begingroup$
You have
$$min_x,y (f(x)+g(y)) leq f(x)+g(y), quad textfor all,, x,y$$
which implies
$$min_x,y (f(x)+g(y)) leq min_x f(x)+ min_y g(y)$$
On the other hand
$$f(x)+g(y) geq min_x f(x) + min_y g(y), quad textfor all,, x,y$$
therefore
$$min_x,y (f(x)+g(y)) geq min_x f(x)+ min_y g(y)$$
So you have the equality.
$endgroup$
You have
$$min_x,y (f(x)+g(y)) leq f(x)+g(y), quad textfor all,, x,y$$
which implies
$$min_x,y (f(x)+g(y)) leq min_x f(x)+ min_y g(y)$$
On the other hand
$$f(x)+g(y) geq min_x f(x) + min_y g(y), quad textfor all,, x,y$$
therefore
$$min_x,y (f(x)+g(y)) geq min_x f(x)+ min_y g(y)$$
So you have the equality.
edited Apr 1 at 20:10
answered Apr 1 at 19:56
RaminRamin
112
112
add a comment |
add a comment |
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