A variational inequality satisfied in a Hilbert space The 2019 Stack Overflow Developer Survey Results Are In Unicorn Meta Zoo #1: Why another podcast? Announcing the arrival of Valued Associate #679: Cesar Manaraprojections in normed linear spacesDistance minimizers in $L^1$ and $L^infty$Maximizing an inner-product over a convex set.On a Variational InequalityComposition of projections has a fixed point in a Hilbert spaceOrthogonal decomposition in Hilbert spacesVariational Inequality only for Real PartInequality with projections in Hilbert SpaceHilbert space $x-P(x)in A^perpRightarrow |x-P(x)|=d(x,A)$Interior solution of a Variational Inequality in Hilbert Space

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A variational inequality satisfied in a Hilbert space



The 2019 Stack Overflow Developer Survey Results Are In
Unicorn Meta Zoo #1: Why another podcast?
Announcing the arrival of Valued Associate #679: Cesar Manaraprojections in normed linear spacesDistance minimizers in $L^1$ and $L^infty$Maximizing an inner-product over a convex set.On a Variational InequalityComposition of projections has a fixed point in a Hilbert spaceOrthogonal decomposition in Hilbert spacesVariational Inequality only for Real PartInequality with projections in Hilbert SpaceHilbert space $x-P(x)in A^perpRightarrow |x-P(x)|=d(x,A)$Interior solution of a Variational Inequality in Hilbert Space










1












$begingroup$


I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:




Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.




This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?










share|cite|improve this question











$endgroup$







  • 2




    $begingroup$
    Puh, what is $q$?
    $endgroup$
    – amsmath
    Mar 24 at 18:52










  • $begingroup$
    my bad $q in V$
    $endgroup$
    – yoshi
    Mar 24 at 19:03










  • $begingroup$
    You should note that $V$ has to be complete, otherwise the projection might not exist.
    $endgroup$
    – gerw
    Mar 25 at 7:10















1












$begingroup$


I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:




Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.




This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?










share|cite|improve this question











$endgroup$







  • 2




    $begingroup$
    Puh, what is $q$?
    $endgroup$
    – amsmath
    Mar 24 at 18:52










  • $begingroup$
    my bad $q in V$
    $endgroup$
    – yoshi
    Mar 24 at 19:03










  • $begingroup$
    You should note that $V$ has to be complete, otherwise the projection might not exist.
    $endgroup$
    – gerw
    Mar 25 at 7:10













1












1








1





$begingroup$


I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:




Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.




This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?










share|cite|improve this question











$endgroup$




I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:




Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.




This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?







real-analysis functional-analysis convex-analysis proof-explanation convex-optimization






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Mar 24 at 19:04







yoshi

















asked Mar 24 at 18:50









yoshiyoshi

1,256917




1,256917







  • 2




    $begingroup$
    Puh, what is $q$?
    $endgroup$
    – amsmath
    Mar 24 at 18:52










  • $begingroup$
    my bad $q in V$
    $endgroup$
    – yoshi
    Mar 24 at 19:03










  • $begingroup$
    You should note that $V$ has to be complete, otherwise the projection might not exist.
    $endgroup$
    – gerw
    Mar 25 at 7:10












  • 2




    $begingroup$
    Puh, what is $q$?
    $endgroup$
    – amsmath
    Mar 24 at 18:52










  • $begingroup$
    my bad $q in V$
    $endgroup$
    – yoshi
    Mar 24 at 19:03










  • $begingroup$
    You should note that $V$ has to be complete, otherwise the projection might not exist.
    $endgroup$
    – gerw
    Mar 25 at 7:10







2




2




$begingroup$
Puh, what is $q$?
$endgroup$
– amsmath
Mar 24 at 18:52




$begingroup$
Puh, what is $q$?
$endgroup$
– amsmath
Mar 24 at 18:52












$begingroup$
my bad $q in V$
$endgroup$
– yoshi
Mar 24 at 19:03




$begingroup$
my bad $q in V$
$endgroup$
– yoshi
Mar 24 at 19:03












$begingroup$
You should note that $V$ has to be complete, otherwise the projection might not exist.
$endgroup$
– gerw
Mar 25 at 7:10




$begingroup$
You should note that $V$ has to be complete, otherwise the projection might not exist.
$endgroup$
– gerw
Mar 25 at 7:10










3 Answers
3






active

oldest

votes


















1












$begingroup$

There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
$$|u - q|^2 = 2 le 5 = |v - q|^2,$$
but
$$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
I suggest finding another proof of this inequality.



But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.



EDIT: Actually, I have a proof of this inequality that I wrote up on hand:




Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
$$langle x - z, c - z rangle le 0 quad forall , c in C$$
if and only if $z = p_C(x)$.




Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
beginalign*
f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
&= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
endalign*

Note that this is a convex quadratic in $lambda$.



Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
$$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
Note that the final inequality also holds for when $c = z = p_C(x)$.



Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
$$|x - c| = f(1) ge f(0) = |x - z|.$$
As this holds for arbitrary $c in C$, we have $z = p_C(x)$.






share|cite|improve this answer











$endgroup$








  • 1




    $begingroup$
    What is $K$ in your example?
    $endgroup$
    – amsmath
    Mar 24 at 19:27










  • $begingroup$
    $K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
    $endgroup$
    – Theo Bendit
    Mar 24 at 19:28










  • $begingroup$
    You should specify it in your example. Otherwise it is incomplete.
    $endgroup$
    – amsmath
    Mar 24 at 19:29











  • $begingroup$
    @amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
    $endgroup$
    – Theo Bendit
    Mar 24 at 20:03










  • $begingroup$
    Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
    $endgroup$
    – amsmath
    Mar 24 at 21:02


















1












$begingroup$

The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.






share|cite|improve this answer









$endgroup$




















    1












    $begingroup$

    I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
    $$ (u - q, v - u ) ge 0 qquad forall v in K$$
    is equivalent to
    $$ |u - q | le | v - q | qquad forall v in K.$$



    The proof is given in the answer by Theo Bendit.



    The second statement is just $u = operatornameproj_K(q)$.






    share|cite|improve this answer









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      3 Answers
      3






      active

      oldest

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      3 Answers
      3






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      1












      $begingroup$

      There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
      $$|u - q|^2 = 2 le 5 = |v - q|^2,$$
      but
      $$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
      I suggest finding another proof of this inequality.



      But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.



      EDIT: Actually, I have a proof of this inequality that I wrote up on hand:




      Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
      $$langle x - z, c - z rangle le 0 quad forall , c in C$$
      if and only if $z = p_C(x)$.




      Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
      beginalign*
      f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
      &= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
      endalign*

      Note that this is a convex quadratic in $lambda$.



      Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
      $$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
      Note that the final inequality also holds for when $c = z = p_C(x)$.



      Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
      $$|x - c| = f(1) ge f(0) = |x - z|.$$
      As this holds for arbitrary $c in C$, we have $z = p_C(x)$.






      share|cite|improve this answer











      $endgroup$








      • 1




        $begingroup$
        What is $K$ in your example?
        $endgroup$
        – amsmath
        Mar 24 at 19:27










      • $begingroup$
        $K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
        $endgroup$
        – Theo Bendit
        Mar 24 at 19:28










      • $begingroup$
        You should specify it in your example. Otherwise it is incomplete.
        $endgroup$
        – amsmath
        Mar 24 at 19:29











      • $begingroup$
        @amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
        $endgroup$
        – Theo Bendit
        Mar 24 at 20:03










      • $begingroup$
        Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
        $endgroup$
        – amsmath
        Mar 24 at 21:02















      1












      $begingroup$

      There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
      $$|u - q|^2 = 2 le 5 = |v - q|^2,$$
      but
      $$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
      I suggest finding another proof of this inequality.



      But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.



      EDIT: Actually, I have a proof of this inequality that I wrote up on hand:




      Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
      $$langle x - z, c - z rangle le 0 quad forall , c in C$$
      if and only if $z = p_C(x)$.




      Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
      beginalign*
      f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
      &= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
      endalign*

      Note that this is a convex quadratic in $lambda$.



      Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
      $$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
      Note that the final inequality also holds for when $c = z = p_C(x)$.



      Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
      $$|x - c| = f(1) ge f(0) = |x - z|.$$
      As this holds for arbitrary $c in C$, we have $z = p_C(x)$.






      share|cite|improve this answer











      $endgroup$








      • 1




        $begingroup$
        What is $K$ in your example?
        $endgroup$
        – amsmath
        Mar 24 at 19:27










      • $begingroup$
        $K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
        $endgroup$
        – Theo Bendit
        Mar 24 at 19:28










      • $begingroup$
        You should specify it in your example. Otherwise it is incomplete.
        $endgroup$
        – amsmath
        Mar 24 at 19:29











      • $begingroup$
        @amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
        $endgroup$
        – Theo Bendit
        Mar 24 at 20:03










      • $begingroup$
        Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
        $endgroup$
        – amsmath
        Mar 24 at 21:02













      1












      1








      1





      $begingroup$

      There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
      $$|u - q|^2 = 2 le 5 = |v - q|^2,$$
      but
      $$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
      I suggest finding another proof of this inequality.



      But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.



      EDIT: Actually, I have a proof of this inequality that I wrote up on hand:




      Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
      $$langle x - z, c - z rangle le 0 quad forall , c in C$$
      if and only if $z = p_C(x)$.




      Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
      beginalign*
      f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
      &= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
      endalign*

      Note that this is a convex quadratic in $lambda$.



      Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
      $$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
      Note that the final inequality also holds for when $c = z = p_C(x)$.



      Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
      $$|x - c| = f(1) ge f(0) = |x - z|.$$
      As this holds for arbitrary $c in C$, we have $z = p_C(x)$.






      share|cite|improve this answer











      $endgroup$



      There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
      $$|u - q|^2 = 2 le 5 = |v - q|^2,$$
      but
      $$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
      I suggest finding another proof of this inequality.



      But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.



      EDIT: Actually, I have a proof of this inequality that I wrote up on hand:




      Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
      $$langle x - z, c - z rangle le 0 quad forall , c in C$$
      if and only if $z = p_C(x)$.




      Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
      beginalign*
      f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
      &= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
      endalign*

      Note that this is a convex quadratic in $lambda$.



      Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
      $$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
      Note that the final inequality also holds for when $c = z = p_C(x)$.



      Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
      $$|x - c| = f(1) ge f(0) = |x - z|.$$
      As this holds for arbitrary $c in C$, we have $z = p_C(x)$.







      share|cite|improve this answer














      share|cite|improve this answer



      share|cite|improve this answer








      edited Mar 24 at 19:30

























      answered Mar 24 at 19:16









      Theo BenditTheo Bendit

      20.9k12355




      20.9k12355







      • 1




        $begingroup$
        What is $K$ in your example?
        $endgroup$
        – amsmath
        Mar 24 at 19:27










      • $begingroup$
        $K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
        $endgroup$
        – Theo Bendit
        Mar 24 at 19:28










      • $begingroup$
        You should specify it in your example. Otherwise it is incomplete.
        $endgroup$
        – amsmath
        Mar 24 at 19:29











      • $begingroup$
        @amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
        $endgroup$
        – Theo Bendit
        Mar 24 at 20:03










      • $begingroup$
        Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
        $endgroup$
        – amsmath
        Mar 24 at 21:02












      • 1




        $begingroup$
        What is $K$ in your example?
        $endgroup$
        – amsmath
        Mar 24 at 19:27










      • $begingroup$
        $K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
        $endgroup$
        – Theo Bendit
        Mar 24 at 19:28










      • $begingroup$
        You should specify it in your example. Otherwise it is incomplete.
        $endgroup$
        – amsmath
        Mar 24 at 19:29











      • $begingroup$
        @amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
        $endgroup$
        – Theo Bendit
        Mar 24 at 20:03










      • $begingroup$
        Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
        $endgroup$
        – amsmath
        Mar 24 at 21:02







      1




      1




      $begingroup$
      What is $K$ in your example?
      $endgroup$
      – amsmath
      Mar 24 at 19:27




      $begingroup$
      What is $K$ in your example?
      $endgroup$
      – amsmath
      Mar 24 at 19:27












      $begingroup$
      $K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
      $endgroup$
      – Theo Bendit
      Mar 24 at 19:28




      $begingroup$
      $K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
      $endgroup$
      – Theo Bendit
      Mar 24 at 19:28












      $begingroup$
      You should specify it in your example. Otherwise it is incomplete.
      $endgroup$
      – amsmath
      Mar 24 at 19:29





      $begingroup$
      You should specify it in your example. Otherwise it is incomplete.
      $endgroup$
      – amsmath
      Mar 24 at 19:29













      $begingroup$
      @amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
      $endgroup$
      – Theo Bendit
      Mar 24 at 20:03




      $begingroup$
      @amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
      $endgroup$
      – Theo Bendit
      Mar 24 at 20:03












      $begingroup$
      Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
      $endgroup$
      – amsmath
      Mar 24 at 21:02




      $begingroup$
      Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
      $endgroup$
      – amsmath
      Mar 24 at 21:02











      1












      $begingroup$

      The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.






      share|cite|improve this answer









      $endgroup$

















        1












        $begingroup$

        The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.






        share|cite|improve this answer









        $endgroup$















          1












          1








          1





          $begingroup$

          The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.






          share|cite|improve this answer









          $endgroup$



          The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Mar 24 at 19:26









          amsmathamsmath

          3,292421




          3,292421





















              1












              $begingroup$

              I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
              $$ (u - q, v - u ) ge 0 qquad forall v in K$$
              is equivalent to
              $$ |u - q | le | v - q | qquad forall v in K.$$



              The proof is given in the answer by Theo Bendit.



              The second statement is just $u = operatornameproj_K(q)$.






              share|cite|improve this answer









              $endgroup$

















                1












                $begingroup$

                I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
                $$ (u - q, v - u ) ge 0 qquad forall v in K$$
                is equivalent to
                $$ |u - q | le | v - q | qquad forall v in K.$$



                The proof is given in the answer by Theo Bendit.



                The second statement is just $u = operatornameproj_K(q)$.






                share|cite|improve this answer









                $endgroup$















                  1












                  1








                  1





                  $begingroup$

                  I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
                  $$ (u - q, v - u ) ge 0 qquad forall v in K$$
                  is equivalent to
                  $$ |u - q | le | v - q | qquad forall v in K.$$



                  The proof is given in the answer by Theo Bendit.



                  The second statement is just $u = operatornameproj_K(q)$.






                  share|cite|improve this answer









                  $endgroup$



                  I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
                  $$ (u - q, v - u ) ge 0 qquad forall v in K$$
                  is equivalent to
                  $$ |u - q | le | v - q | qquad forall v in K.$$



                  The proof is given in the answer by Theo Bendit.



                  The second statement is just $u = operatornameproj_K(q)$.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered Mar 25 at 7:12









                  gerwgerw

                  20.1k11334




                  20.1k11334



























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