Rudi Pendavingh
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Registered User
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Dec 12 |
comment |
How to solve a system of quadratic equations over finite fields? If you write your vectors $d_i$ as the rows of a matrix $D$, then unless I misread something your problem is to find, given matrices $G$ and $H$, a vector $y$ and a matrix $D$ such that $$HDGy=0.$$ I guess you want $D,y$ nonzero? Or do you want all such $D,y$. |
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Dec 9 |
revised |
Convex optimization problem to QPP added 4 characters in body |
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Dec 8 |
revised |
Convex optimization problem to QPP deleted 2 characters in body |
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Dec 8 |
revised |
Convex optimization problem to QPP edited body |
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Dec 8 |
revised |
Convex optimization problem to QPP added 754 characters in body |
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Dec 8 |
awarded | ● Commentator |
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Dec 8 |
comment |
Convex optimization problem to QPP Adding $F_i(x)\geq 0$ will introduce restrictions on $x$ that are not in your original problem. |
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Dec 8 |
revised |
Convex optimization problem to QPP deleted 16 characters in body |
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Dec 8 |
answered | Convex optimization problem to QPP |
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Dec 8 |
awarded | ● Enthusiast |
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Dec 5 |
comment |
linear independence of finite binary sequences Do you really want your collection of vectors `$\{x_1,\ldots, x_n\}$' to be unordered? |
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Nov 26 |
accepted | A certain type of quadratic problem. |
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Nov 23 |
comment |
A certain type of quadratic problem. Actually, you will have $\{u\in U∣ u^HAu=0}\neq \emptyset$ for all linear combinations $A$ of $A_,\ldots,A_k$. But still that is not enough to force a common point I guess. |
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Nov 23 |
comment |
A certain type of quadratic problem. I expect that there are examples with two constraints $u^HA_iu=0$ where there is a gap. My argument to close the gap really breaks when there are more constraints. Each set $\{u\in U\mid u^HA_iu=0\}$ will be nonempty, but there need not be a common point to all these sets. |
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Nov 22 |
comment |
A certain type of quadratic problem. Well, if you have a method at your disposal for computing the smallest eigenvalue of a Hermitian matrix, then you can evaluate $\lambda(t)$ for any $t$. As $t\mapsto\lambda(t)$ is concave, solving $\max_t \lambda(t)$ can be done by standard methods, say bisection. |
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Nov 22 |
revised |
A certain type of quadratic problem. deleted 1 characters in body |
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Nov 22 |
answered | A certain type of quadratic problem. |
