bio  website  regularize.wordpress.com 

location  Braunschweig, Germany  
age  36  
visits  member for  4 years, 6 months 
seen  9 hours ago  
stats  profile views  1,886 
Professor at TU Braunschweig.
Area: Inverse problems, regularization theory, applied functional analysis, mathematical image processing.
2d

comment 
Hadamard / matrix product adjoint
Ok, I see now. I think a better fit for this question would be scicomp.stackexchange.com. Anyway: The adjoint is defined by $\langle A^* y,x\rangle = \langle y,Ax\rangle$. You do adjoints one by one from outside to inside. 
Mar 26 
comment 
Hadamard / matrix product adjoint
Sorry, but this does not make sense. What is the Hadamard product of the matrix S and the vector Fx? 
Mar 26 
comment 
Hadamard / matrix product adjoint
Err... So x is a matrix? 
Mar 26 
comment 
Hadamard / matrix product adjoint
I could not parse your definition of the operator A. If D and S are matrices, do you build the Hadamard product with the matrix of the Fourier transform? 
Mar 26 
comment 
Convergence in energy of bounded (semi)subharmonic functions
Sorry for the late reply: I guess the best thing would be to write an answer yourself so that this is kept for the records. 
Mar 17 
comment 
Fredholm integral with functions constrained to [0;1]
For some reason I confused $g$ and $f$. Of course $f$ should be the unknown… Corrected. 
Mar 16 
comment 
Fredholm integral with functions constrained to [0;1]
The most simple thing that comes to mind is the projected gradient method, see my update. 
Feb 27 
comment 
What is an extragradient method?
Well, this shows that the term "extragradient" is indeed used differently. 
Feb 19 
comment 
Different styles of writing/reading articles
@FedericoPoloni I agree. When I wrote the comment, this question was closed without an answer, so it was unclear if it would ever get any answers here… 
Feb 19 
comment 
Different styles of writing/reading articles
Probably this question will get answers over at academia.stackexchange.com 
Feb 17 
comment 
How to solve the following generalized quadratic programming problem
Well its still convex, albeit nonsmooth. Looks like primaldual methods, alternating direction method of multipliers or so could be applied… 
Feb 2 
comment 
optimization of inverse matrix with constraint on matrix elements
Have you tried to formulate the optimality system, e.g. by using this: en.wikipedia.org/wiki/… 
Jan 27 
comment 
Reference : Special case of Banachvalued function integration by parts
I would start looking in Zeidler's books on functional analysis but I don't have access right now. 
Jan 25 
comment 
Phase of the inner product between the elements of an ETF
Hmm you can multiply any frame element with any complex number of modulus one and still get another ETF. But well this changes all the inner products so probably you won't get an arbitrary distribution... 
Jan 25 
comment 
Recent trends in effective analysis
I suggest that you copy the titles of the references in the Wikipedia article into, e.g., Google Scholar and look for recent works that cite these works. Seems like there are plenty... 
Jan 9 
comment 
Are there any with Erdös number 1 on mathoverflow?
Evidence: "Coloring graphs with locally few colors" by P. Erdõs, Z. Füredi, A. Hajnal, P. Komjáth, V. Rödl, Á. Seress, Discrete Math., 59(1986), cs.elte.hu/~kope/localcoloring.pdf 
Jan 5 
comment 
What is the advantage of the knowledge of jumps for approximating a function with trigonometric polynomials?
For the first method there is no convergence in the supnorm (Gibbs phenomenon). 
Jan 4 
comment 
distribution discretization
I suspect that you will not have approximation in the total variation distance but only weak approximation. Probably this can be quantified by Prokhorov or Wasserstein metrics but I don't know a good pointer... 
Jan 4 
comment 
Does removing some constraints in convex program change the optimal solution?
Jupp, this is also true in two variables. 
Dec 29 
comment 
Finding sparsest solution of a linear system
Some good heuristics go under the name "pursuit", e.g. (regularized) (orthogonal) matching pursuit or basis pursuit. 