July 7-12, 2024. Andrew Barron is the Shannon Lecturer. Plenary talks by Venkat Guruswami, Emina Soljanin, Rebecca Willett, and Gregory Wornell. Workshops: IT for Trustworthy ML, DNA-based data storage, IT in Neuroscience... , Quantum Info Knowledge, and Learning to compress.
@CihanPostsThms In what axiomatic system? Since CH is independent of ZFC, this would seem to imply that (1) cannot be proven in ZFC. Does the result generalize to systems (e.g., ZFC + other axioms) where the CH is either true or false?
@ProfKinyon What axioms are you using for set theory? ZFC also says "nah" (https://t.co/dHudV9Bjbk) but Frege's set theory says yup but is inconsistent
@MountainOfMoon Indeed, this is a very cool result. I would also add that their theorem lower bounds the "sharpness" by an increasing function of the minimum distance. So, one might say that every sequence of codes whose minimum distance grows without bound has a sharp threshold.
So glad I won't need to find a new place for my research science updates 😀 (twitter: you can turn down the revenue rate now... it seems like my feed has been crammed with ads lately)
The Shannon award to Rudiger Urbanke is both terrific news and a long overdue recognition to one of the most influential information and coding theorists of the last quarter century. 1/n
@ccanonne_ Going from Bernoulli (or Binomial) to Gaussian is also a standard trick for Efron-Stein -> Poincare and Hypercontractivity: https://t.co/GpoU2NABhV
For anti-concentration, see Theorem 6 in https://t.co/ESwmW2ITs2
@ccanonne_ You might get from Poisson to Gaussian by noting that a centered normalized Poisson converges in distribution to a standard Gaussian: https://t.co/f1phGNBWul
@lpachter This sounds like a suggestion to teach continuous-time discrete-valued jump Markov processes before teaching basic calculus. For some simple models, this is possible but the intuition behind many important concepts (e.g., generating functions) really requires calculus.
@ProbFact I think this needs to be stated more precisely. For an n-vector of std Gaussians with large n, the squared Euclidean dist to the mean concentrates around n+o(n). Defining the std deviation as the sqrt of this, the Euclidean dist is less than 2 sqrt(n) with prob 1 as n increases
@lupusorina @gautamcgoel Have you ever gone out to eat in Zurich? Not that like McDonald's but a Zurich big mac is $14 while an USA big mac is $6
https://t.co/hjeySnROIs
Very honored to receive this award along with such an excellent group of collaborators: Shrinivas Kudekar, Santhosh Kumar, Marco Mondelli, Eren Şaşoǧlu and Rüdiger Urbanke
On Tuesday, at the first congressional hearing to investigate the January 6 Capitol insurrection, Capitol Police Officer Harry Dunn delivered powerful testimony:
“Telling the truth shouldn't be hard. Fighting on January 6, that was hard.”
More: https://t.co/BT8bmlV6xl