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Jan
22
revised Determinant of non-square Jacobian
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Jan
22
asked Determinant of non-square Jacobian
Jan
22
revised The differential of a symmetric matrix in terms of its eigen-decomposition
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Jan
21
comment Calculus: tricky integration problem.
you're overthinking this, there are many $g(x)$ which will work, all you need to do is find one. Use the fact that you can pull constants outside the integral.
Jan
21
comment Calculus: tricky integration problem.
consider $f(x) = (x^3-x)g(x)$, and now figure out what $g(x)$ could be.
Jan
13
comment Is $\log \det \left( I + \frac 1 {\sigma^2} H F \bar H \right)$ concave?
you mean the conjugate transpose?
Jan
13
comment Is $\log \det \left( I + \frac 1 {\sigma^2} H F \bar H \right)$ concave?
what is $\bar{H}$?
Jan
13
comment Solution of quadratic optimization with linear constraints
probably Lagrange multipliers then
Jan
13
comment Solution of quadratic optimization with linear constraints
are you expected to solve it analytically? or is this a specific problem with numerical values?
Jan
13
comment The differential of a symmetric matrix in terms of its eigen-decomposition
you're right that is interesting, but is there a way to use it to prove the formula above?
Jan
13
comment The differential of a symmetric matrix in terms of its eigen-decomposition
@user1952009, as far as I can tell this doesn't get me anything new.
Jan
13
revised The differential of a symmetric matrix in terms of its eigen-decomposition
added 32 characters in body
Jan
13
revised The differential of a symmetric matrix in terms of its eigen-decomposition
added 32 characters in body
Jan
13
asked The differential of a symmetric matrix in terms of its eigen-decomposition
Jan
13
accepted Given an algebraic curve $F(x,y)=0$, why do the partial derivatives of $F(x,y)$ being zero at a point imply the plane curve has a singularity?
Jan
13
accepted Hidden Markov Model Coin Toss Problem
Jan
12
comment Reference on properties of binary random vectors
This isn't really about random matrices. We're going to need to know more about exactly what you're looking for, as it stands what you're asking for is too broad and vague. Random vectors are just n-variate random variables and they are basically studied everywhere in probability and statistics.
Jan
12
revised Reference on properties of binary random vectors
edited tags
Jan
6
comment Non Zero Function .Differomophism.
because $Df$ is linear and invertible it's an isomorphism of groups and thus must take the identity to identity.
Jan
6
comment Could someone offer an explanation of $x^{10} \equiv 1 \pmod{11}$?
look up Fermat's Little Theorem.