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A polynomial threshold function (PTF) $f:\mathbb{R}^n \rightarrow \mathbb{R}$ is a function of the form $f(x) = \mathsf{sign}(p(x))$ where $p$ is a polynomial of degree at most $d$. PTFs are a classical and well-studied complexity class…

Computational Complexity · Computer Science 2021-11-30 Zander Kelley , Raghu Meka

Particularly in genomics, but also in other fields, it has become commonplace to undertake highly multiple Student's $t$-tests based on relatively small sample sizes. The literature on this topic is continually expanding, but the main…

Statistics Theory · Mathematics 2010-10-11 Peter Hall , Qiying Wang

Agreement tests are a generalization of low degree tests that capture a local-to-global phenomenon, which forms the combinatorial backbone of most PCP constructions. In an agreement test, a function is given by an ensemble of local…

Computational Complexity · Computer Science 2020-12-14 Irit Dinur , Yuval Filmus , Prahladh Harsha

We improve certain degree bounds for Grobner bases of polynomial ideals in generic position. We work exclusively in deterministically verifiable and achievable generic positions of a combinatorial nature, namely either strongly stable…

Symbolic Computation · Computer Science 2017-05-09 Amir Hashemi , Werner M. Seiler

Graph-based tests are a class of non-parametric two-sample tests useful for analyzing high-dimensional data. The test statistics are constructed from similarity graphs (such as K-minimum spanning tree), and consequently, their performance…

Methodology · Statistics 2025-06-23 Yichuan Bai , Lynna Chu

We obtain upper bounds, independent of the ambient dimension, for the number of realizable zero-nonzero patterns and (over ordered fields) sign conditions of a finite family of polynomials $\mathcal P$ restricted to an algebraic subset $V$…

Combinatorics · Mathematics 2026-01-05 Saugata Basu , Laxmi Parida

The $\epsilon$-approximate degree of a function $f\colon X \to \{0, 1\}$ is the least degree of a multivariate real polynomial $p$ such that $|p(x)-f(x)| \leq \epsilon$ for all $x \in X$. We determine the $\epsilon$-approximate degree of…

Computational Complexity · Computer Science 2019-09-18 Alexander A. Sherstov , Justin Thaler

In [2], the authors prove Stillman's conjecture in all characteristics and all degrees by showing that, independent of the algebraically closed field $K$ or the number of variables, $n$ forms of degree at most $d$ in a polynomial ring $R$…

Commutative Algebra · Mathematics 2020-05-25 Tigran Ananyan , Melvin Hochster

Rubinfeld & Vasilyan recently introduced the framework of testable learning as an extension of the classical agnostic model. It relaxes distributional assumptions which are difficult to verify by conditions that can be checked efficiently…

Machine Learning · Computer Science 2024-11-07 Lucas Slot , Stefan Tiegel , Manuel Wiedmer

We consider the construction of maximal families of polynomials over the finite field $\mathbb{F}_q$, all having the same degree $n$ and a nonzero constant term, where the degree of the GCD of any two polynomials is $d$ with $1 \le d\le n$.…

Discrete Mathematics · Computer Science 2024-05-15 Maximilien Gadouleau , Luca Mariot , Federico Mazzone

One of the main problems in random network coding is to compute good lower and upper bounds on the achievable cardinality of the so-called subspace codes in the projective space $\mathcal{P}_q(n)$ for a given minimum distance. The…

Information Theory · Computer Science 2020-11-16 Tao Feng , Sascha Kurz , Shuangqing Liu

Consider the problem of constructing an experimental design, optimal for estimating parameters of a given statistical model with respect to a chosen criterion. To address this problem, the literature usually provides a single solution.…

Computation · Statistics 2024-11-05 Radoslav Harman , Lenka Filová , Samuel Rosa

In confirmatory clinical trials with small sample sizes, hypothesis tests based on asymptotic distributions are often not valid and exact non-parametric procedures are applied instead. However, the latter are based on discrete test…

Methodology · Statistics 2018-02-22 Robin Ristl , Dong Xi , Ekkehard Glimm , Martin Posch

Equivalence testing, a fundamental problem in the field of distribution testing, seeks to infer if two unknown distributions on $[n]$ are the same or far apart in the total variation distance. Conditional sampling has emerged as a powerful…

Data Structures and Algorithms · Computer Science 2024-03-08 Diptarka Chakraborty , Sourav Chakraborty , Gunjan Kumar , Kuldeep S. Meel

We consider the goodness-of-fit testing problem of distinguishing whether the data are drawn from a specified distribution, versus a composite alternative separated from the null in the total variation metric. In the discrete case, we…

Statistics Theory · Mathematics 2017-07-03 Sivaraman Balakrishnan , Larry Wasserman

We propose a method for verifying that a given feasible point for a polynomial optimization problem is globally optimal. The approach relies on the Lasserre hierarchy and the result of Lasserre regarding the importance of the convexity of…

Optimization and Control · Mathematics 2021-01-05 Sikun Xu , Ruoyi Ma , Daniel K. Molzahn , Hassan Hijazi , Cédric Josz

Submodular and fractionally subadditive (or equivalently XOS) functions play a fundamental role in combinatorial optimization, algorithmic game theory and machine learning. Motivated by learnability of these classes of functions from random…

Data Structures and Algorithms · Computer Science 2015-08-04 Vitaly Feldman , Jan Vondrak

For a fixed polynomial $\Delta$, we study the number of polynomials $f$ of degree $n$ over $\mathbb F_q$ such that $f$ and $f+\Delta$ are both irreducible, an $\mathbb F_q[T]$-analogue of the twin primes problem. In the large-$q$ limit, we…

Number Theory · Mathematics 2024-10-15 Ofir Gorodetsky , Will Sawin

We consider the question of learning $Q$-function in a sample efficient manner for reinforcement learning with continuous state and action spaces under a generative model. If $Q$-function is Lipschitz continuous, then the minimal sample…

Machine Learning · Computer Science 2020-06-12 Devavrat Shah , Dogyoon Song , Zhi Xu , Yuzhe Yang

In the \textsc{Maximum Degree Contraction} problem, input is a graph $G$ on $n$ vertices, and integers $k, d$, and the objective is to check whether $G$ can be transformed into a graph of maximum degree at most $d$, using at most $k$ edge…

Data Structures and Algorithms · Computer Science 2020-09-25 Saket Saurabh , Prafullkumar Tale
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