7,113 reputation
1544
bio website case.edu/artsci/math/mwmeckes
location Cleveland, Ohio
age 38
visits member for 5 years, 9 months
seen 10 hours ago

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