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In this work we study zero vs. epsilon-error capacity in network coding instances. For multicast network coding it is well known that all rates that can be delivered with arbitrarily small error probability can also be delivered with zero…

Information Theory · Computer Science 2015-03-19 Michael Langberg , Michelle Effros

The problem of joint universal source coding and identification is considered in the setting of fixed-rate lossy coding of continuous-alphabet memoryless sources. For a wide class of bounded distortion measures, it is shown that any…

Information Theory · Computer Science 2007-07-13 Maxim Raginsky

Let $F(X)= \prod_{i=1}^k(a_iX+b_i)$ be a polynomial with $a_i, b_i$ being integers. Suppose the discriminant of $F$ is non-zero and $F$ is admissible. Given any natural number $N$, let $S(F,N)$ denotes those integers less than or equal to…

Number Theory · Mathematics 2014-04-01 Gyan Prakash

Clustering has many important applications in computer science, but real-world datasets often contain outliers. Moreover, the presence of outliers can make the clustering problems to be much more challenging. To reduce the complexities,…

Data Structures and Algorithms · Computer Science 2020-05-04 Hu Ding , Jiawei Huang , Haikuo Yu

For sink-free orientations in graphs of minimum degree at least $3$, we show that there is a deterministic approximate counting algorithm that runs in time $O((n^{73}/\varepsilon^{72})\log(n/\varepsilon))$, a near-linear time sampling…

Data Structures and Algorithms · Computer Science 2025-02-17 Konrad Anand , Graham Freifeld , Heng Guo , Chunyang Wang , Jiaheng Wang

We identify a new notion of pseudorandomness for randomness sources, which we call the average bias. Given a distribution $Z$ over $\{0,1\}^n$, its average bias is: $b_{\text{av}}(Z) =2^{-n} \sum_{c \in \{0,1\}^n} |\mathbb{E}_{z \sim…

Computational Complexity · Computer Science 2019-05-31 Arnab Bhattacharyya , Philips George John , Suprovat Ghoshal , Raghu Meka

Let $\xi_0,\xi_1,\ldots$ be i.i.d. random variables with zero mean and unit variance. Consider a random Taylor series of the form $f(z)=\sum_{k=0}^\infty \xi_k c_k z^k$, where $c_0,c_1,\ldots$ is a real sequence such that $c_n^2$ is…

Probability · Mathematics 2017-10-05 Hendrik Flasche , Zakhar Kabluchko

For any $T \geq 1$, there are constants $R=R(T) \geq 1$ and $\zeta=\zeta(T)>0$ and a randomized algorithm that takes as input an integer $n$ and two strings $x,y$ of length at most $n$, and runs in time $O(n^{1+\frac{1}{T}})$ and outputs an…

Data Structures and Algorithms · Computer Science 2019-05-10 Michal Koucký , Michael E. Saks

Randomness extractors, widely used in classical and quantum cryptography and other fields of computer science, e.g., derandomization, are functions which generate almost uniform randomness from weak sources of randomness. In the quantum…

Quantum Physics · Physics 2025-06-09 Rotem Arnon , Christopher Portmann , Volkher B. Scholz

Blind methods often separate or identify signals or signal subspaces up to an unknown scaling factor. Sometimes it is necessary to cope with the scaling ambiguity, which can be done through reconstructing signals as they are received by…

Sound · Computer Science 2017-08-02 Zbyněk Koldovský , Francesco Nesta

We describe random processes (with binary alphabet) whose entropy is less than 1 (per letter), but they mimic true random process, i.e., by definition, generated sequence can be interpreted as the result of the flips of a fair coin with…

Information Theory · Computer Science 2015-12-23 Boris Ryabko

A reduction of a source distribution is a collection of smaller sized distributions that are collectively equivalent to the source distribution with respect to the property of decomposability. That is, an arbitrary language is decomposable…

Systems and Control · Computer Science 2018-03-30 Liyong Lin , Tomáš Masopust , W. Murray Wonham , Rong Su

We develop a new method to constraint primordial non-Gaussianities of the local kind using unclustered tracers of the Large Scale Structure. We show that in the limit of low noise, zero bias tracers yield large improvement over standard…

Cosmology and Nongalactic Astrophysics · Physics 2018-09-12 Emanuele Castorina , Yu Feng , Uros Seljak , Francisco Villaescusa-Navarro

Let $s$ denote a distinguished source vertex of a non-negatively real weighted and undirected graph $G$ with $n$ vertices and $m$ edges. In this paper we present two efficient \emph{single-source approximate-distance sensitivity oracles},…

Data Structures and Algorithms · Computer Science 2016-08-18 Davide Bilò , Luciano Gualà , Stefano Leucci , Guido Proietti

We study in details the bias and variance of the entropy estimator proposed by Kozachenko and Leonenko for a large class of densities on $\mathbb{R}^d$. We then use the work of Bickel and Breiman to prove a central limit theorem in…

Statistics Theory · Mathematics 2016-02-25 Nicolas Fournier , Sylvain Delattre

The entropy or randomness source is an essential ingredient in random number generation. Quantum random number generators generally require well modeled and calibrated light sources, such as a laser, to generate randomness. With…

We present Vibrato Nonnegative Tensor Factorization, an algorithm for single-channel unsupervised audio source separation with an application to separating instrumental or vocal sources with nonstationary pitch from music recordings. Our…

Sound · Computer Science 2016-06-02 Elliot Creager , Noah D. Stein , Roland Badeau , Philippe Depalle

For $x\ge y>1$ and $u:= \log x/\log y$, let $\Phi(x,y)$ denote the number of positive integers up to $x$ free of prime divisors less than or equal to $y$. In 1950 de Bruijn [1] studied the approximation of $\Phi(x,y)$ by the quantity…

Number Theory · Mathematics 2023-10-04 Steve Fan

This article introduces trimmed estimators for the mean and covariance function of general functional data. The estimators are based on a new measure of outlyingness or data depth that is well defined on any metric space, although this…

Methodology · Statistics 2012-12-03 Daniel Gervini

Given an $n$-point metric space $(\mathcal{X},d)$ where each point belongs to one of $m=O(1)$ different categories or groups and a set of integers $k_1, \ldots, k_m$, the fair Max-Min diversification problem is to select $k_i$ points…

Data Structures and Algorithms · Computer Science 2022-01-19 Raghavendra Addanki , Andrew McGregor , Alexandra Meliou , Zafeiria Moumoulidou
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