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We present an amelioration of current known algorithms for optimal spectral partitioning problems. The idea is to use the advantage of a representation using density functions while decreasing the computational time. This is done by…

Optimization and Control · Mathematics 2017-05-25 Beniamin Bogosel

Despite the relevance of the binomial distribution for probability theory and applied statistical inference, its higher-order moments are poorly understood. The existing formulas are either not general enough, or not structured and…

Statistics Theory · Mathematics 2022-06-07 Maciej Skorski

The $2 \rightarrow q$ norm of a matrix $X \in \mathbb{R}^{n \times d}$ is defined as $\lVert X \rVert_{2 \rightarrow q} = \sup_{\lVert v \rVert_2 = 1} \lVert Xv \rVert_q$. We give polynomial-time multiplicative approximation algorithms for…

Data Structures and Algorithms · Computer Science 2026-05-29 Samuel B. Hopkins , Stefan Tiegel

We study a graph partitioning problem motivated by the simulation of the physical movement of multi-body systems on an atomistic level, where the forces are calculated from a quantum mechanical description of the electrons. Several advanced…

We enhance the approximation capabilities of algebraic polynomials by composing them with homeomorphisms. This composition yields families of functions that remain dense in the space of continuous functions, while enabling more accurate…

Numerical Analysis · Mathematics 2025-12-17 Álvaro Fernández Corral , Yahya Saleh

Counting problems, determining the number of possible states of a large system under certain constraints, play an important role in many areas of science. They naturally arise for complex disordered systems in physics and chemistry, in…

Statistical Mechanics · Physics 2009-05-15 Marc Timme , Frank van Bussel , Denny Fliegner , Sebastian Stolzenberg

Symmetric submodular functions are an important family of submodular functions capturing many interesting cases including cut functions of graphs and hypergraphs. Maximization of such functions subject to various constraints receives little…

Data Structures and Algorithms · Computer Science 2016-04-19 Moran Feldman

In this paper, we study first-order methods on a large variety of low-rank matrix optimization problems, whose solutions only live in a low dimensional eigenspace. Traditional first-order methods depend on the eigenvalue decomposition at…

Optimization and Control · Mathematics 2019-04-25 Yongfeng Li , Haoyang Liu , Zaiwen Wen , Yaxiang Yuan

The problem of testing low-degree polynomials has received significant attention over the years due to its importance in theoretical computer science, and in particular in complexity theory. The problem is specified by three parameters:…

Computational Complexity · Computer Science 2022-02-18 Tali Kaufman , Dor Minzer

We formalize the problem of selecting the optimal set of options for planning as that of computing the smallest set of options so that planning converges in less than a given maximum of value-iteration passes. We first show that the problem…

Artificial Intelligence · Computer Science 2019-03-19 Yuu Jinnai , David Abel , D Ellis Hershkowitz , Michael Littman , George Konidaris

This paper presents a novel stochastic barrier function (SBF) framework for safety analysis of stochastic systems based on piecewise (PW) functions. We first outline a general formulation of PW-SBFs. Then, we focus on PW-Constant (PWC) SBFs…

Robotics · Computer Science 2024-10-24 Rayan Mazouz , Frederik Baymler Mathiesen , Luca Laurenti , Morteza Lahijanian

Polynomial functions have plenty of useful analytical properties, but they are rarely used as learning models because their function class is considered to be restricted. This work shows that when trained properly polynomial functions can…

Machine Learning · Computer Science 2021-06-30 Li-Ping Liu , Ruiyuan Gu , Xiaozhe Hu

The problem of finding a nontrivial factor of a polynomial f(x) over a finite field F_q has many known efficient, but randomized, algorithms. The deterministic complexity of this problem is a famous open question even assuming the…

Computational Complexity · Computer Science 2019-02-20 Manuel Arora , Gábor Ivanyos , Marek Karpinski , Nitin Saxena

One fundamental goal of high-dimensional statistics is to detect or recover planted structure (such as a low-rank matrix) hidden in noisy data. A growing body of work studies low-degree polynomials as a restricted model of computation for…

Statistics Theory · Mathematics 2022-06-22 Tselil Schramm , Alexander S. Wein

We develop a pseudo-random generator to fool degree-$d$ polynomial threshold functions with respect to the Gaussian distribution. For $c>0$ any constant, we construct a pseudo-random generator that fools such functions to within $\epsilon$…

Computational Complexity · Computer Science 2011-04-08 Daniel M. Kane

We prove two main results on how arbitrary linear threshold functions $f(x) = \sign(w\cdot x - \theta)$ over the $n$-dimensional Boolean hypercube can be approximated by simple threshold functions. Our first result shows that every…

Computational Complexity · Computer Science 2009-10-21 Ilias Diakonikolas , Rocco A. Servedio

We set new speed records for multiplying long polynomials over finite fields of characteristic two. Our multiplication algorithm is based on an additive FFT (Fast Fourier Transform) by Lin, Chung, and Huang in 2014 comparing to previously…

Symbolic Computation · Computer Science 2018-01-08 Ming-Shing Chen , Chen-Mou Cheng , Po-Chun Kuo , Wen-Ding Li , Bo-Yin Yang

It is well known that, using fast algorithms for polynomial multiplication and division, evaluation of a polynomial $F \in \mathbb{C}[x]$ of degree $n$ at $n$ complex-valued points can be done with $\tilde{O}(n)$ exact field operations in…

Numerical Analysis · Computer Science 2016-05-30 Alexander Kobel , Michael Sagraloff

The fastest known algorithm for factoring a degree $n$ univariate polynomial over a finite field $\mathbb{F}_q$ runs in time $O(n^{3/2 + o(1)}\text{polylog } q)$, and there is a reason to believe that the $3/2$ exponent represents a…

Data Structures and Algorithms · Computer Science 2025-11-17 Chris Umans , Siki Wang

When computing bounds, spatial branch-and-bound algorithms often linearly outer approximate convex relaxations for non-convex expressions in order to capitalize on the efficiency and robustness of linear programming solvers. Considering…

Optimization and Control · Mathematics 2025-12-22 William R. Strahl , Arvind U. Raghunathan , Nikolaos V. Sahinidis , Chrysanthos E. Gounaris