Zobrazeno 1 - 10
of 1 064
pro vyhledávání: '"A. Ordentlich"'
We observe an infinite sequence of independent identically distributed random variables $X_1,X_2,\ldots$ drawn from an unknown distribution $p$ over $[n]$, and our goal is to estimate the entropy $H(p)=-\mathbb{E}[\log p(X)]$ within an $\varepsilon$-
Externí odkaz:
http://arxiv.org/abs/2406.06312
Autor:
Klartag, Bo'az, Ordentlich, Or
Let $\nu$ and $\mu$ be probability distributions on $\mathbb{R}^n$, and $\nu_s,\mu_s$ be their evolution under the heat flow, that is, the probability distributions resulting from convolving their density with the density of an isotropic Gaussian ran
Externí odkaz:
http://arxiv.org/abs/2406.03427
It has been known for a long time that the mutual information between the input sequence and output of a binary symmetric channel (BSC) is upper bounded by the mutual information between the same input sequence and the output of a binary erasure chan
Externí odkaz:
http://arxiv.org/abs/2401.14710
The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a function of the number of available samples, with far less atte
Externí odkaz:
http://arxiv.org/abs/2312.15225
Let $K$ be a convex body in $\mathbb{R}^n$, let $L$ be a lattice with covolume one, and let $\eta>0$. We say that $K$ and $L$ form an $\eta$-smooth cover if each point $x \in \mathbb{R}^n$ is covered by $(1 \pm \eta) vol(K)$ translates of $K$ by $L$.
Externí odkaz:
http://arxiv.org/abs/2311.04644
In this paper we consider the problem of uniformity testing with limited memory. We observe a sequence of independent identically distributed random variables drawn from a distribution $p$ over $[n]$, which is either uniform or is $\varepsilon$-far f
Externí odkaz:
http://arxiv.org/abs/2206.09395
In this paper we consider the problem of estimating a Bernoulli parameter using finite memory. Let $X_1,X_2,\ldots$ be a sequence of independent identically distributed Bernoulli random variables with expectation $\theta$, where $\theta \in [0,1]$. C
Externí odkaz:
http://arxiv.org/abs/2206.09390
This paper studies the sample complexity of learning the $k$ unknown centers of a balanced Gaussian mixture model (GMM) in $\mathbb{R}^d$ with spherical covariance matrix $\sigma^2\mathbf{I}$. In particular, we are interested in the following questio
Externí odkaz:
http://arxiv.org/abs/2202.07707
In a growing number of applications, there is a need to digitize a (possibly high) number of correlated signals whose spectral characteristics are challenging for traditional analog-to-digital converters (ADCs). Examples, among others, include multip
Externí odkaz:
http://arxiv.org/abs/2110.06183
Autor:
Romanov, Elad, Ordentlich, Or
Publikováno v:
Proceedings of The 25th International Conference on Artificial Intelligence and Statistics, PMLR 151:1298-1320, 2022
Consider the rank-1 spiked model: $\bf{X}=\sqrt{\nu}\xi \bf{u}+ \bf{Z}$, where $\nu$ is the spike intensity, $\bf{u}\in\mathbb{S}^{k-1}$ is an unknown direction and $\xi\sim \mathcal{N}(0,1),\bf{Z}\sim \mathcal{N}(\bf{0},\bf{I})$. Motivated by recent
Externí odkaz:
http://arxiv.org/abs/2110.01150