[HTML][HTML] Log-concavity and strong log-concavity: a review
A Saumard, JA Wellner - Statistics surveys, 2014 - ncbi.nlm.nih.gov
We review and formulate results concerning log-concavity and strong-log-concavity in both
discrete and continuous settings. We show how preservation of log-concavity and strongly …
discrete and continuous settings. We show how preservation of log-concavity and strongly …
Forward and reverse entropy power inequalities in convex geometry
The entropy power inequality, which plays a fundamental role in information theory and
probability, may be seen as an analogue of the Brunn-Minkowski inequality. Motivated by …
probability, may be seen as an analogue of the Brunn-Minkowski inequality. Motivated by …
Count-min: Optimal estimation and tight error bounds using empirical error distributions
D Ting - Proceedings of the 24th ACM SIGKDD International …, 2018 - dl.acm.org
The Count-Min sketch is an important and well-studied data summarization method. It can
estimate the count of any item in a stream using a small, fixed size data sketch. However, the …
estimate the count of any item in a stream using a small, fixed size data sketch. However, the …
Feature allocations, probability functions, and paintboxes
The problem of inferring a clustering of a data set has been the subject of much research in
Bayesian analysis, and there currently exists a solid mathematical foundation for Bayesian …
Bayesian analysis, and there currently exists a solid mathematical foundation for Bayesian …
Why the rich get richer? On the balancedness of random partition models
Random partition models are widely used in Bayesian methods for various clustering tasks,
such as mixture models, topic models, and community detection problems. While the …
such as mixture models, topic models, and community detection problems. While the …
The discrete moment problem with nonconvex shape constraints
The discrete moment problem is a foundational problem in distribution-free robust
optimization, where the goal is to find a worst-case distribution that satisfies a given set of …
optimization, where the goal is to find a worst-case distribution that satisfies a given set of …
Rogozin's convolution inequality for locally compact groups
General extensions of an inequality due to Rogozin, concerning the essential supremum of
a convolution of probability density functions on the real line, are obtained. While a weak …
a convolution of probability density functions on the real line, are obtained. While a weak …
Multiobjective optimization of crewed spacecraft supportability strategies
AC Owens - 2019 - dspace.mit.edu
Future crewed missions present a logistical challenge that is unprecedented in human
spaceflight. Astronauts will travel farther from Earth than ever before, and stay in space for …
spaceflight. Astronauts will travel farther from Earth than ever before, and stay in space for …
Entropy and the discrete central limit theorem
L Gavalakis, I Kontoyiannis - Stochastic Processes and their Applications, 2024 - Elsevier
A strengthened version of the central limit theorem for discrete random variables is
established, relying only on information-theoretic tools and elementary arguments. It is …
established, relying only on information-theoretic tools and elementary arguments. It is …
Bernoulli sums and Rényi entropy inequalities
Bernoulli sums and Rényi entropy inequalities Page 1 Bernoulli 29(2), 2023, 1578–1599
https://doi.org/10.3150/22-BEJ1511 Bernoulli sums and Rényi entropy inequalities MOKSHAY …
https://doi.org/10.3150/22-BEJ1511 Bernoulli sums and Rényi entropy inequalities MOKSHAY …