Zobrazeno 1 - 10
of 5 395
pro vyhledávání: '"Concentration inequality"'
Autor:
Alon, Noga, Gravin, Nick, Pollner, Tristan, Rubinstein, Aviad, Wang, Hongao, Weinberg, S. Matthew, Zhang, Qianfan
We investigate prophet inequalities with competitive ratios approaching $1$, seeking to generalize $k$-uniform matroids. We first show that large girth does not suffice: for all $k$, there exists a matroid of girth $\geq k$ and a prophet inequality i
Externí odkaz:
http://arxiv.org/abs/2411.11741
Autor:
Houdré, Christian
Via a covariance representation based on characteristic functions, a known elementary proof of the Gaussian concentration inequality is presented. A few other applications are briefly mentioned.
Comment: These simple notes on well known results
Comment: These simple notes on well known results
Externí odkaz:
http://arxiv.org/abs/2410.06937
In this paper, we study the stability of the concentration inequality for one-dimensional complex polynomials. We provide the stability of the local concentration inequality and a global version using a Wehrl-type entropy.
Externí odkaz:
http://arxiv.org/abs/2408.07424
Autor:
Eller, Katharina, Freyer, Ansgar
An affine version of the linear subspace concentration inequality as proposed by Wu is established for centered convex bodies. This generalizes results from Wu and Freyer, Henk, Kipp on polytopes to convex bodies.
Externí odkaz:
http://arxiv.org/abs/2407.17799
Autor:
Danielsson, Joel Larsson
Given a finite set $S$, i.i.d. random weights $\{X_i\}_{i\in S}$, and a family of subsets $\mathcal{F}\subseteq 2^S$, we consider the minimum weight of an $F\in \mathcal{F}$: \[ M(\mathcal{F}):= \min_{F\in \mathcal{F}} \sum_{i\in F}X_i. \] In particu
Externí odkaz:
http://arxiv.org/abs/2407.12672
Autor:
Ni, Yijin, Huo, Xiaoming
Maximum Mean Discrepancy (MMD) is a probability metric that has found numerous applications in machine learning. In this work, we focus on its application in generative models, including the minimum MMD estimator, Generative Moment Matching Network (
Externí odkaz:
http://arxiv.org/abs/2405.14051
Autor:
Chikr Elmezouar, Zouaoui1 (AUTHOR) zchikrelmezouar@kku.edu.sa, Belguerna, Abderrahmane2 (AUTHOR) belguerna@cuniv-naama.dz, Daoudi, Hamza3 (AUTHOR) daoudi.hamza@univ-bechar.dz, Alshahrani, Fatimah4 (AUTHOR) fmalshahrani@pnu.edu.sa, Kaddour, Zoubeyr2 (AUTHOR)
Publikováno v:
Axioms (2075-1680). Aug2024, Vol. 13 Issue 8, p511. 14p.
Akademický článek
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Akademický článek
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Autor:
Zouaoui Chikr Elmezouar, Abderrahmane Belguerna, Hamza Daoudi, Fatimah Alshahrani, Zoubeyr Kaddour
Publikováno v:
Axioms, Vol 13, Iss 8, p 511 (2024)
This paper introduces an innovative concentration inequality for Extended Negative Dependence (END) random variables, providing new insights into their almost complete convergence. We apply this inequality to analyze END variable sequences, particula
Externí odkaz:
https://doaj.org/article/65063dd2c8134a2f944438f1fdae256f