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We consider the problem of finding exact sums of squares (SOS) decompositions for certain classes of non-negative multivariate polynomials, relying on semidefinite programming (SDP) solvers. We start by providing a hybrid numeric-symbolic…

Symbolic Computation · Computer Science 2018-03-01 Victor Magron , Mohab Safey El Din

A recent breakthrough in Edmonds' problem showed that the noncommutative rank can be computed in deterministic polynomial time, and various algorithms for it were devised. However, only quite complicated algorithms are known for finding a…

Data Structures and Algorithms · Computer Science 2022-07-19 Cole Franks , Tasuku Soma , Michel X. Goemans

We use the Sum of Squares method to develop new efficient algorithms for learning well-separated mixtures of Gaussians and robust mean estimation, both in high dimensions, that substantially improve upon the statistical guarantees achieved…

Data Structures and Algorithms · Computer Science 2017-11-21 Samuel B. Hopkins , Jerry Li

In Bayesian probabilistic programming, a central problem is to estimate the normalised posterior distribution (NPD) of a probabilistic program with conditioning via score (a.k.a. observe) statements. Most previous approaches address this…

Programming Languages · Computer Science 2024-08-02 Peixin Wang , Tengshun Yang , Hongfei Fu , Guanyan Li , C. -H. Luke Ong

This paper describes an algorithm (thus far referred to as the "Dragonfly Algorithm") by which the subset-sum problem can be solved in $O(n^{11}\log(n))$ time complexity. The paper will first detail the generalized "product-derivative"…

Computational Complexity · Computer Science 2022-12-08 Rion Tolchin

The Moment/Sum-of-squares hierarchy provides a way to compute the global minimizers of polynomial optimization problems (POP), at the cost of solving a sequence of increasingly large semidefinite programs (SDPs). We consider large-scale…

Optimization and Control · Mathematics 2023-09-13 Johannes Aspman , Gilles Bareilles , Vyacheslav Kungurtsev , Jakub Marecek , Martin Takáč

In subset selection we search for the best linear predictor that involves a small subset of variables. From a computational complexity viewpoint, subset selection is NP-hard and few classes are known to be solvable in polynomial time. Using…

Optimization and Control · Mathematics 2020-02-07 Alberto Del Pia , Santanu S. Dey , Robert Weismantel

We revisit the classic #Knapsack problem, which asks to count the Boolean points $(x_1,\dots,x_n)\in\{0,1\}^n$ in a given half-space $\sum_{i=1}^nW_ix_i\le T$. This #P-complete problem admits $(1\pm\epsilon)$-approximation. Before this…

Data Structures and Algorithms · Computer Science 2024-10-30 Weiming Feng , Ce Jin

We consider the Subset Sum Ratio Problem ($SSR$), in which given a set of integers the goal is to find two subsets such that the ratio of their sums is as close to~1 as possible, and introduce a family of variations that capture additional…

Data Structures and Algorithms · Computer Science 2020-03-17 Nikolaos Melissinos , Aris Pagourtzis , Theofilos Triommatis

In the Nonnegative Matrix Factorization (NMF) problem we are given an $n \times m$ nonnegative matrix $M$ and an integer $r > 0$. Our goal is to express $M$ as $A W$ where $A$ and $W$ are nonnegative matrices of size $n \times r$ and $r…

Data Structures and Algorithms · Computer Science 2011-11-04 Sanjeev Arora , Rong Ge , Ravi Kannan , Ankur Moitra

This article presents a strongly polynomial-time algorithm for the general linear programming problem. This algorithm is an implicit reduction procedure that works as follows. Primal and dual problems are combined into a special system of…

Optimization and Control · Mathematics 2026-03-24 Samuel Awoniyi

Given a fixed arity $k \geq 2$, Min-$k$-CSP on complete instances involves a set of $n$ variables $V$ and one nontrivial constraint for every $k$-subset of variables (so there are $\binom{n}{k}$ constraints). The goal is to find an…

Data Structures and Algorithms · Computer Science 2024-10-28 Aditya Anand , Euiwoong Lee , Amatya Sharma

We present a new method for solving the hidden polynomial graph problem (HPGP) which is a special case of the hidden polynomial problem (HPP). The new approach yields an efficient quantum algorithm for the bivariate HPGP even when the input…

Quantum Physics · Physics 2022-02-01 Thomas Decker , Peter Hoyer , Gabor Ivanyos , Miklos Santha

Let $\R$ be a real closed field, $ {\mathcal Q} \subset \R[Y_1,...,Y_\ell,X_1,...,X_k], $ with $ \deg_{Y}(Q) \leq 2, \deg_{X}(Q) \leq d, Q \in {\mathcal Q}, #({\mathcal Q})=m$, and $ {\mathcal P} \subset \R[X_1,...,X_k] $ with $\deg_{X}(P)…

Geometric Topology · Mathematics 2010-10-21 Saugata Basu , Dmitrii V. Pasechnik , Marie-Françoise Roy

Let $A$ be an $(m \times n)$ integral matrix, and let $P=\{ x : A x \leq b\}$ be an $n$-dimensional polytope. The width of $P$ is defined as $ w(P)=min\{ x\in \mathbb{Z}^n\setminus\{0\} :\: max_{x \in P} x^\top u - min_{x \in P} x^\top v…

Computational Geometry · Computer Science 2022-11-30 Dmitry Gribanov , Sergey Veselov

We show the first unconditional pseudo-determinism result for all of search-BPP. Specifically, we show that every BPP search problem can be computed pseudo-deterministically on average for infinitely many input lengths. In other words, for…

Computational Complexity · Computer Science 2017-07-20 Dhiraj Holden

Given a multiset $X=\{x_1,..., x_n\}$ of real numbers, the {\it floating-point set summation} problem asks for $S_n=x_1+...+x_n$. Let $E^*_n$ denote the minimum worst-case error over all possible orderings of evaluating $S_n$. We prove that…

Data Structures and Algorithms · Computer Science 2024-09-21 Ming-Yang Kao , Jie Wang

In this paper, we study the Dynamic Parameterized Subset Sampling (DPSS) problem in the Word RAM model. In DPSS, the input is a set,~$S$, of~$n$ items, where each item,~$x$, has a non-negative integer weight,~$w(x)$. Given a pair of query…

Data Structures and Algorithms · Computer Science 2024-09-27 Junhao Gan , Seeun William Umboh , Hanzhi Wang , Anthony Wirth , Zhuo Zhang

The problem of optimizing over the cone of nonnegative polynomials is a fundamental problem in computational mathematics, with applications to polynomial optimization, control, machine learning, game theory, and combinatorics, among others.…

Optimization and Control · Mathematics 2018-06-20 Georgina Hall

We present three deterministic parameterized algorithms for well-studied packing and matching problems, namely, Weighted q-Dimensional p-Matching ((q,p)-WDM) and Weighted q-Set p-Packing ((q,p)-WSP). More specifically, we present an…

Data Structures and Algorithms · Computer Science 2013-11-19 Meirav Zehavi
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