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We study the probabilistic degree over reals of the OR function on $n$ variables. For an error parameter $\epsilon$ in (0,1/3), the $\epsilon$-error probabilistic degree of any Boolean function $f$ over reals is the smallest non-negative…

Computational Complexity · Computer Science 2022-11-24 Siddharth Bhandari , Prahladh Harsha , Tulasimohan Molli , Srikanth Srinivasan

The determinantal complexity of a polynomial $P \in \mathbb{F}[x_1, \ldots, x_n]$ over a field $\mathbb{F}$ is the dimension of the smallest matrix $M$ whose entries are affine functions in $\mathbb{F}[x_1, \ldots, x_n]$ such that $P =…

Computational Complexity · Computer Science 2021-12-03 Mrinal Kumar , Ben Lee Volk

We study the complexity of representing polynomials as a sum of products of polynomials in few variables. More precisely, we study representations of the form $$P = \sum_{i = 1}^T \prod_{j = 1}^d Q_{ij}$$ such that each $Q_{ij}$ is an…

Computational Complexity · Computer Science 2015-04-24 Mrinal Kumar , Shubhangi Saraf

We characterize the limiting distributions of random variables of the form $P_n\left( (X_i)_{i \ge 1} \right)$, where: (i) $(P_n)_{n \ge 1}$ is a sequence of multivariate polynomials, each potentially involving countably many variables;…

Probability · Mathematics 2024-12-10 Ronan Herry , Dominique Malicet , Guillaume Poly

We study the problem of testing whether a function $f: \mathbb{R}^n \to \mathbb{R}$ is a polynomial of degree at most $d$ in the \emph{distribution-free} testing model. Here, the distance between functions is measured with respect to an…

Data Structures and Algorithms · Computer Science 2022-04-19 Vipul Arora , Arnab Bhattacharyya , Noah Fleming , Esty Kelman , Yuichi Yoshida

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

In this paper we investigate the uniform distribution properties of polynomials in many variables and bounded degree over a fixed finite field F of prime order. Our main result is that a polynomial P : F^n -> F is poorly-distributed only if…

Combinatorics · Mathematics 2007-11-21 Ben Green , Terence Tao

A pair of probability distributions over $\{0,1\}^n$ is said to be $(k,\delta)$-wise indistinguishable if all of the size $k$ marginals are within statistical distance at most $\delta$. Previous works introduced this concept and study when…

Computational Complexity · Computer Science 2026-05-14 Christopher Williamson

If one seeks to estimate the total variation between two product measures $||P^\otimes_{1:n}-Q^\otimes_{1:n}||$ in terms of their marginal TV sequence $\delta=(||P_1-Q_1||,||P_2-Q_2||,\ldots,||P_n-Q_n||)$, then trivial upper and lower…

Probability · Mathematics 2024-10-03 Aryeh Kontorovich

We consider the following basic, and very broad, statistical problem: Given a known high-dimensional distribution ${\cal D}$ over $\mathbb{R}^n$ and a collection of data points in $\mathbb{R}^n$, distinguish between the two possibilities…

Computational Complexity · Computer Science 2024-11-25 Anindya De , Huan Li , Shivam Nadimpalli , Rocco A. Servedio

For a sample of absolutely bounded i.i.d. random variables with a continuous density the cumulative distribution function of the sample variance is represented by a univariate integral over a Fourier series. If the density is a polynomial…

Statistics Theory · Mathematics 2008-10-10 T. Royen

In this work, we establish lower-bounds against memory bounded algorithms for distinguishing between natural pairs of related distributions from samples that arrive in a streaming setting. In our first result, we show that any algorithm…

Computational Complexity · Computer Science 2020-02-19 Sumegha Garg , Pravesh K. Kothari , Ran Raz

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

Let $X$ be a random variable with distribution function $F,$ and $X_{1},X_{2},...,X_{n}$ are independent copies of $X.$ Consider the order statistics $X_{i:n},$ $i=1,2,...,n$ and denote $F_{i:n}(x)=P\{X_{i:n}\leq x\}.$ Using majorization…

Statistics Theory · Mathematics 2011-09-02 Ismihan Bairamov

The probabilistic degree of a Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ is defined to be the smallest $d$ such that there is a random polynomial $\mathbf{P}$ of degree at most $d$ that agrees with $f$ at each point with high…

Computational Complexity · Computer Science 2019-10-08 Srikanth Srinivasan , Utkarsh Tripathi , S. Venkitesh

Polynomials are common algebraic structures, which are often used to approximate functions including probability distributions. This paper proposes to directly define polynomial distributions in order to describe stochastic properties of…

Information Theory · Computer Science 2022-12-12 Yue Yu , Pavel Loskot

We show how to compute any symmetric Boolean function on $n$ variables over any field (as well as the integers) with a probabilistic polynomial of degree $O(\sqrt{n \log(1/\epsilon)})$ and error at most $\epsilon$. The degree dependence on…

Data Structures and Algorithms · Computer Science 2016-11-18 Josh Alman , Ryan Williams

An $(n, k)$-Poisson Multinomial Distribution (PMD) is a random variable of the form $X = \sum_{i=1}^n X_i$, where the $X_i$'s are independent random vectors supported on the set of standard basis vectors in $\mathbb{R}^k.$ In this paper, we…

Data Structures and Algorithms · Computer Science 2016-06-23 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

We consider the problem of learning an unknown product distribution $X$ over $\{0,1\}^n$ using samples $f(X)$ where $f$ is a \emph{known} transformation function. Each choice of a transformation function $f$ specifies a learning problem in…

Machine Learning · Computer Science 2011-03-04 Constantinos Daskalakis , Ilias Diakonikolas , Rocco A. Servedio

Polynomial regression is a basic primitive in learning and statistics. In its most basic form the goal is to fit a degree $d$ polynomial to a response variable $y$ in terms of an $n$-dimensional input vector $x$. This is extremely…

Data Structures and Algorithms · Computer Science 2020-04-30 Sitan Chen , Raghu Meka
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