3,543 reputation
11951
bio website regularize.wordpress.com
location Braunschweig, Germany
age 36
visits member for 4 years, 9 months
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Professor at TU Braunschweig.

Area: Inverse problems, regularization theory, applied functional analysis, mathematical image processing.


Jan
13
revised How to find the generic initial ideal?
format edited
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 sup-norm (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
revised Does removing some constraints in convex program change the optimal solution?
added 98 characters in body
Jan
4
comment Does removing some constraints in convex program change the optimal solution?
Jupp, this is also true in two variables.
Jan
4
answered Does removing some constraints in convex program change the optimal solution?
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.
Dec
26
comment An inequality concerning restricted isometry property
If you only have $supp(x) \subset S_1$ and $supp(y) \subset S_2$ then no lower bound greater than zero is to be expected and even if you have non-trivial intersection of the supports then the inner product can well be zero, I guess.
Dec
21
comment Open problems in compressed sensing
One thing is that it makes a huge difference if one answers this question as a mathematician or as an engineer. Well, of course this is site for mathematics but the idea of compressed sensing is really a practical one: get information about a high dimensional object that lives in lower dimensional but nonlinear subspace from few measurements. The meaning of all ingredients is debatable here and varies a lot from problem to problem. Hence one open problem is to find the right mathematical formulation of the problem...
Dec
19
comment Image of (right) inverse trace map $\xi\colon H^{\frac 12}(\partial\Omega) \to H^1(\Omega)$ dense in $H^1(\Omega)$?
Ok, right - I thought that I had a basic misconception about the problem…
Dec
19
comment journal to submit mathematic books' review
The German "Mathematische Semesterberichte" publishes such reviews (probably only in German).
Dec
19
reviewed Close How to construct a graph with arbitrarily large girth and large chromatic number?
Dec
19
reviewed Leave Open Image of (right) inverse trace map $\xi\colon H^{\frac 12}(\partial\Omega) \to H^1(\Omega)$ dense in $H^1(\Omega)$?
Dec
19
comment Image of (right) inverse trace map $\xi\colon H^{\frac 12}(\partial\Omega) \to H^1(\Omega)$ dense in $H^1(\Omega)$?
Isn't solving the respective Dirichlet problem saying that the image contains $H^{3/2}$?
Dec
16
reviewed Close Alexander duality theorem
Dec
11
revised What is an extragradient method?
corrected spelling
Dec
10
answered Galerkin Projection on Integral Operators
Dec
10
answered What is an extragradient method?
Dec
7
comment Banach space of discontinuous functions(Killing continuous functions)
"Appropriate quotient space" Do you have an idea how this space looks like (or how the space which you divide by)? I guess the quotient contains all characteristic functions of all points and then it wouldn't be separable in the first norm. The second norm looks pretty weired to me…