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An $(n,k)$-Poisson Multinomial Distribution (PMD) is the distribution of the sum of $n$ independent random vectors supported on the set ${\cal B}_k=\{e_1,\ldots,e_k\}$ of standard basis vectors in $\mathbb{R}^k$. We prove a structural…

Data Structures and Algorithms · Computer Science 2015-11-24 Constantinos Daskalakis , Gautam Kamath , Christos Tzamos

An $(n,k)$-Poisson Multinomial Distribution (PMD) is the distribution of the sum of $n$ independent random vectors supported on the set ${\cal B}_k=\{e_1,\ldots,e_k\}$ of standard basis vectors in $\mathbb{R}^k$. We show that any…

Data Structures and Algorithms · Computer Science 2016-06-17 Constantinos Daskalakis , Anindya De , Gautam Kamath , Christos Tzamos

The Poisson multinomial distribution (PMD) describes the distribution of the sum of $n$ independent but non-identically distributed random vectors, in which each random vector is of length $m$ with 0/1 valued elements and only one of its…

Computation · Statistics 2022-01-13 Zhengzhi Lin , Yueyao Wang , Yili Hong

We give an algorithm for properly learning Poisson binomial distributions. A Poisson binomial distribution (PBD) of order $n$ is the discrete probability distribution of the sum of $n$ mutually independent Bernoulli random variables. Given…

Data Structures and Algorithms · Computer Science 2015-11-13 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

We consider a basic problem in unsupervised learning: learning an unknown \emph{Poisson Binomial Distribution}. A Poisson Binomial Distribution (PBD) over $\{0,1,\dots,n\}$ is the distribution of a sum of $n$ independent Bernoulli random…

Data Structures and Algorithms · Computer Science 2015-02-18 Constantinos Daskalakis , Ilias Diakonikolas , Rocco A. Servedio

We introduce the problem of simultaneously learning all powers of a Poisson Binomial Distribution (PBD). A PBD of order $n$ is the distribution of a sum of $n$ mutually independent Bernoulli random variables $X_i$, where $\mathbb{E}[X_i] =…

Data Structures and Algorithms · Computer Science 2017-07-19 Dimitris Fotakis , Vasilis Kontonis , Piotr Krysta , Paul Spirakis

We investigate the complexity of computing approximate Nash equilibria in anonymous games. Our main algorithmic result is the following: For any $n$-player anonymous game with a bounded number of strategies and any constant $\delta>0$, an…

Computer Science and Game Theory · Computer Science 2016-08-29 Yu Cheng , Ilias Diakonikolas , Alistair Stewart

In this paper, we consider the extensively studied problem of computing a $k$-sparse approximation to the $d$-dimensional Fourier transform of a length $n$ signal. Our algorithm uses $O(k \log k \log n)$ samples, is dimension-free, operates…

Data Structures and Algorithms · Computer Science 2019-09-26 Vasileios Nakos , Zhao Song , Zhengyu Wang

We consider the problem of computing the k-sparse approximation to the discrete Fourier transform of an n-dimensional signal. We show: * An O(k log n)-time randomized algorithm for the case where the input signal has at most k non-zero…

Data Structures and Algorithms · Computer Science 2012-04-09 Haitham Hassanieh , Piotr Indyk , Dina Katabi , Eric Price

We consider the well-studied Sparse Fourier transform problem, where one aims to quickly recover an approximately Fourier $k$-sparse vector $\widehat{x} \in \mathbb{C}^{n^d}$ from observing its time domain representation $x$. In the exact…

Data Structures and Algorithms · Computer Science 2023-01-24 Karl Bringmann , Michael Kapralov , Mikhail Makarov , Vasileios Nakos , Amir Yagudin , Amir Zandieh

For all $n, \epsilon >0$, we show that the set of Poisson Binomial distributions on $n$ variables admits a proper $\epsilon$-cover in total variation distance of size $n^2+n \cdot (1/\epsilon)^{O(\log^2 (1/\epsilon))}$, which can also be…

Computation · Statistics 2014-10-03 Constantinos Daskalakis , Christos Papadimitriou

We present a Fourier transform methodology for all-order polarization mode dispersion (PMD) analysis, based on the first Born approximation to the coupled-mode equation solution. Our method predicts wavelength-dependent PMD effects and…

Optics · Physics 2007-05-23 Michael C. Parker , Etienne Rochat , Stuart D. Walker

We show that there is a polynomial-time approximation scheme for computing Nash equilibria in anonymous games with any fixed number of strategies (a very broad and important class of games), extending the two-strategy result of Daskalakis…

Computer Science and Game Theory · Computer Science 2016-11-15 Constantinos Daskalakis , Christos H. Papadimitriou

We consider the problem of computing a $k$-sparse approximation to the Fourier transform of a length $N$ signal. Our main result is a randomized algorithm for computing such an approximation (i.e. achieving the $\ell_2/\ell_2$ sparse…

Data Structures and Algorithms · Computer Science 2016-04-05 Michael Kapralov

A Poisson Binomial distribution over $n$ variables is the distribution of the sum of $n$ independent Bernoullis. We provide a sample near-optimal algorithm for testing whether a distribution $P$ supported on $\{0,...,n\}$ to which we have…

Data Structures and Algorithms · Computer Science 2014-10-15 Jayadev Acharya , Constantinos Daskalakis

This note presents a rigorous introduction to a selection of distributions along with their Fourier transforms, which are commonly encountered in signal processing and, in particular, magnetic resonance imaging (MRI). In contrast to many…

Functional Analysis · Mathematics 2025-06-24 Kaibo Tang

We study the structure and learnability of sums of independent integer random variables (SIIRVs). For $k \in \mathbb{Z}_{+}$, a $k$-SIIRV of order $n \in \mathbb{Z}_{+}$ is the probability distribution of the sum of $n$ independent random…

Data Structures and Algorithms · Computer Science 2015-11-24 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

The Discrete Fourier Transform (DFT) is a fundamental computational primitive, and the fastest known algorithm for computing the DFT is the FFT (Fast Fourier Transform) algorithm. One remarkable feature of FFT is the fact that its runtime…

Data Structures and Algorithms · Computer Science 2019-02-28 Michael Kapralov , Ameya Velingker , Amir Zandieh

The Poisson distribution of order $k$ is a special case of a compound Poisson distribution. For $k=1$ it is the standard Poisson distribution. Our main result is a proof that for sufficiently small values of the rate parameter $\lambda$,…

Probability · Mathematics 2023-10-03 S. R. Mane

A $k$-modal probability distribution over the discrete domain $\{1,...,n\}$ is one whose histogram has at most $k$ "peaks" and "valleys." Such distributions are natural generalizations of monotone ($k=0$) and unimodal ($k=1$) probability…

Data Structures and Algorithms · Computer Science 2014-09-16 Constantinos Daskalakis , Ilias Diakonikolas , Rocco A. Servedio
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