bio | website | case.edu/artsci/math/mwmeckes |
---|---|---|
location | Cleveland, Ohio | |
age | 38 | |
visits | member for | 5 years, 10 months |
seen | Aug 22 at 19:58 | |
stats | profile views | 4,314 |
Assoc. Prof. at CWRU. My main research interests are in probability, geometry, and functional analysis.
Jul
24 |
revised |
Do subgaussian variables obey the slightly-stronger-than-Chernoff tail bound?
Fixed inequalities. |
Jul
23 |
answered | Do subgaussian variables obey the slightly-stronger-than-Chernoff tail bound? |
Jul
20 |
answered | Extending GUE to a measure on operators? |
Jul
6 |
awarded | Good Question |
Jun
30 |
comment |
Kullback Leibler “variance”: does that divergence have a name?
I haven't seen exactly this quantity considered, but something related is studied here (see in particular the discussion after Theorem 1.1): projecteuclid.org/euclid.aop/1312555807 |
Jun
30 |
comment |
Shared maximum eigenvector
For an appropriate interpretation of the question, at least. The OP said $v$ is "the" eigenvector associated to the maximum eigenvalue of $A$, but if the eigenspace is not 1-dimensional you may need to replace $v$ with another eigenvector. |
May
27 |
comment |
Higher Moments, what are they good for?
Essentially the same question was asked and answered here: stats.stackexchange.com/questions/2893/… |
May
27 |
comment |
Describe the desired features of a “Mathematics Colloquium”?
A former department chair of mine used to say that if you asked colloquium speakers to prepare talks appropriate for undergraduates, then there was a chance some of the faculty would understand. |
May
6 |
awarded | Popular Question |
May
5 |
awarded | Notable Question |
Mar
26 |
comment |
Is there an introduction to probability theory from a structuralist/categorical perspective?
@MartinBrandenburg: Moreover, I would need convincing that probability theory is about the category of probability spaces and measurable maps. That category surely plays a role, but most of what's of interest in the theory seems to take place outside of it. In particular, if you can show me how to view the law of large numbers or the central limit theorem as being about the category of probability spaces and measurable maps, then I'll reconsider. |
Mar
26 |
comment |
Is there an introduction to probability theory from a structuralist/categorical perspective?
@MartinBrandenburg: I don't claim that it's distracting to define graphs as pairs of sets. I claim that if you do get distracted by the details of such a definition, then you're not doing graph theory. |
Nov
14 |
comment |
Best possible concentration inequality in high dimensions
Ah, or by $\|X_i\|_2 \le 1$ did you mean that the Euclidean norm of $X_i$ is almost surely at most 1? I thought you were referring to the $L^2$ norm of a random variable. In that case, you can e.g. use a vector-valued version of Talagrand's inequality to get the same type of result as the one dimensional case. |
Nov
14 |
comment |
Best possible concentration inequality in high dimensions
Yes, in 1 dimension this is Hoeffding's inequality if you have boundedness, but that was never mentioned. |
Nov
12 |
comment |
Best possible concentration inequality in high dimensions
You need additional assumptions, even in the one-dimensional case, for Hoeffding's inequality to hold. |
Oct
22 |
awarded | Yearling |
Sep
30 |
awarded | Explainer |
Jul
17 |
comment |
Clusters of uniformly distributed random points
@ChristianRemling: for the most part, MathSciNet only lists citations from papers indexed in MathSciNet beginning sometime in the 1990s, so it misses almost all citations older than that and many newer ones as well. (It looks like Naus's paper has lots of citations from papers in other fields.) |
Jul
3 |
comment |
Nonexistence of stable random variables
I think I really should just read Feller straight through one of these days. |
Jul
2 |
awarded | Curious |