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Related papers: Testing noisy low-degree polynomials for sparsity

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Let $f:\{-1,1\}^n$ be a polynomial with at most $s$ non-zero real coefficients. We give an algorithm for exactly reconstructing f given random examples from the uniform distribution on $\{-1,1\}^n$ that runs in time polynomial in $n$ and…

Machine Learning · Computer Science 2014-11-10 Murat Kocaoglu , Karthikeyan Shanmugam , Alexandros G. Dimakis , Adam Klivans

We study the problem of robust multivariate polynomial regression: let $p\colon\mathbb{R}^n\to\mathbb{R}$ be an unknown $n$-variate polynomial of degree at most $d$ in each variable. We are given as input a set of random samples…

Data Structures and Algorithms · Computer Science 2024-03-15 Vipul Arora , Arnab Bhattacharyya , Mathews Boban , Venkatesan Guruswami , Esty Kelman

A low-degree test is a collection of simple, local rules for checking the proximity of an arbitrary function to a low-degree polynomial. Each rule depends on the function's values at a small number of places. If a function satisfies many…

Computational Complexity · Computer Science 2013-07-16 Katalin Friedl , Madhu Sudan

In this work, we consider the sample complexity required for testing the monotonicity of distributions over partial orders. A distribution $p$ over a poset is monotone if, for any pair of domain elements $x$ and $y$ such that $x \preceq y$,…

Data Structures and Algorithms · Computer Science 2019-07-09 Maryam Aliakbarpour , Themis Gouleakis , John Peebles , Ronitt Rubinfeld , Anak Yodpinyanee

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

We study an infinite class of sequences of sparse polynomials that have binomial coefficients both as exponents and as coefficients. This generalizes a sequence of sparse polynomials which arises in a natural way as graph theoretic…

Classical Analysis and ODEs · Mathematics 2020-08-05 Karl Dilcher , Maciej Ulas

Over the past decade, the low-degree heuristic has been used to estimate the algorithmic thresholds for a wide range of average-case planted vs null distinguishing problems. Such results rely on the hypothesis that if the low-degree moments…

Computational Complexity · Computer Science 2026-01-12 Jun-Ting Hsieh , Daniel M. Kane , Pravesh K. Kothari , Jerry Li , Sidhanth Mohanty , Stefan Tiegel

We study when low coordinate degree functions (LCDF) -- linear combinations of functions depending on small subsets of entries of a vector -- can hypothesis test between high-dimensional probability measures. These functions are a…

Statistics Theory · Mathematics 2024-03-13 Dmitriy Kunisky

We characterize the set of properties of Boolean-valued functions on a finite domain $\mathcal{X}$ that are testable with a constant number of samples. Specifically, we show that a property $\mathcal{P}$ is testable with a constant number…

Data Structures and Algorithms · Computer Science 2016-12-20 Eric Blais , Yuichi Yoshida

A function $f : \mathbb{F}_2^n \to \mathbb{R}$ is $s$-sparse if it has at most $s$ non-zero Fourier coefficients. Motivated by applications to fast sparse Fourier transforms over $\mathbb{F}_2^n$, we study efficient algorithms for the…

Data Structures and Algorithms · Computer Science 2019-10-15 Grigory Yaroslavtsev , Samson Zhou

We reveal a complexity chasm, separating the trinomial and tetranomial cases, for solving univariate sparse polynomial equations over certain local fields. First, for any fixed field $K\in\{\mathbb{Q}_2,\mathbb{Q}_3,\mathbb{Q}_5,\ldots\}$,…

Number Theory · Mathematics 2021-06-08 J. Maurice Rojas , Yuyu Zhu

In this paper, we propose two new interpolation algorithms for sparse multivariate polynomials represented by a straight-line program(SLP). Both of our algorithms work over any finite fields $F_q$ with large characteristic. The first one is…

Symbolic Computation · Computer Science 2020-02-11 Qiao-Long Huang

This work presents a new variation of the commonly used Least Mean Squares Algorithm (LMS) for the identification of sparse signals with an a-priori known sparsity using a hard threshold operator in every iteration. It examines some useful…

Systems and Control · Computer Science 2016-08-04 Lampros Flokas , Petros Maragos

Recently, it has been observed that a sparse trigonometric polynomial, i.e. having only a small number of non-zero coefficients, can be reconstructed exactly from a small number of random samples using Basis Pursuit (BP) or Orthogonal…

Numerical Analysis · Mathematics 2008-04-06 Holger Rauhut

Robust mean estimation is one of the most important problems in statistics: given a set of samples in $\mathbb{R}^d$ where an $\alpha$ fraction are drawn from some distribution $D$ and the rest are adversarially corrupted, we aim to…

Machine Learning · Computer Science 2022-12-07 Shiwei Zeng , Jie Shen

Assume that we observe a sample of size n composed of p-dimensional signals, each signal having independent entries drawn from a scaled Poisson distribution with an unknown intensity. We are interested in estimating the sum of the n unknown…

Statistics Theory · Mathematics 2018-01-19 Olivier Collier , Arnak Dalalyan

For a polynomial $f$ from a class $\mathcal{C}$ of polynomials, we show that the problem to compute all the constant degree irreducible factors of $f$ reduces in polynomial time to polynomial identity tests (PIT) for class $\mathcal{C}$ and…

Computational Complexity · Computer Science 2026-03-02 Pranjal Dutta , Amit Sinhababu , Thomas Thierauf

We establish how the coefficients of a sparse polynomial system influence the sum (or the trace) of its zeros. As an application, we develop numerical tests for verifying whether a set of solutions to a sparse system is complete. These…

Algebraic Geometry · Mathematics 2022-01-14 Taylor Brysiewicz , Michael Burr

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

In this paper, we investigate property testing whether or not a degree d multivariate poly- nomial is a sum of squares or is far from a sum of squares. We show that if we require that the property tester always accepts YES instances and…

Computational Complexity · Computer Science 2017-09-12 Aaron Potechin , Liu Yang