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This paper will analyze several quadratic-time solvable problems, and will classify them into two classes: problems that are solvable in truly subquadratic time (that is, in time $O(n^{2-\epsilon})$ for some $\epsilon>0$) and problems that…

Computational Complexity · Computer Science 2014-07-21 Michele Borassi , Pierluigi Crescenzi , Michel Habib

Solving linear systems of equations is ubiquitous in all areas of science and engineering. With rapidly growing data sets, such a task can be intractable for classical computers, as the best known classical algorithms require a time…

This chapter delves into the realm of computational complexity, exploring the world of challenging combinatorial problems and their ties with statistical physics. Our exploration starts by delving deep into the foundations of combinatorial…

Disordered Systems and Neural Networks · Physics 2023-10-04 Raffaele Marino

We present an efficient quantum algorithm to simulate nonlinear differential equations with polynomial vector fields of arbitrary degree on quantum platforms. Models of physical systems that are governed by ordinary differential equations…

Dynamical Systems · Mathematics 2023-02-08 Amit Surana , Abeynaya Gnanasekaran , Tuhin Sahai

This paper begins with a class of convex quadratic programs (QPs) with bounded variables solvable by the parametric principal pivoting algorithm with $\mathcal{O}(n^3)$ strongly polynomial complexity, where $n$ is the number of variables of…

Optimization and Control · Mathematics 2022-09-28 Jong-Shi Pang , Shaoning Han

Many learning algorithms are formulated in terms of finding model parameters which minimize a data-fitting loss function plus a regularizer. When the regularizer involves the l0 pseudo-norm, the resulting regularization path consists of a…

Machine Learning · Computer Science 2020-03-06 Toby Hocking , Joseph Vargovich

In this paper, we propose a probabilistic algorithm suitable for any linear code $C$ to determine whether a given vector $\mathbf{x}$ belongs to $ C$. The algorithm achieves $O(n\log n)$ time complexity, $ O(n^2)$ space complexity and with…

Information Theory · Computer Science 2026-01-06 Mingchao Li , Jiyou Li

For a prime $p>3$, let $D$ be the discriminant of an imaginary quadratic order with $|D|< \frac{4}{\sqrt{3}}\sqrt{p}$. We research the solutions of the class polynomial $H_D(X)$ mod $p$ in $\mathbb{F}_p$ if $D$ is not a quadratic residue in…

Number Theory · Mathematics 2021-03-09 Guanju Xiao , Lixia Luo , Yingpu Deng

We show that the existence of a computationally efficient calibration algorithm, with a low weak calibration rate, would imply the existence of an efficient algorithm for computing approximate Nash equilibria - thus implying the unlikely…

Computer Science and Game Theory · Computer Science 2012-02-23 Elad Hazan , Sham Kakade

In a recent article, the class of functions from the integers to the integers computable in polynomial time has been characterized using discrete ordinary differential equations (ODE), also known as finite differences. Doing so, we pointed…

Computational Complexity · Computer Science 2022-10-04 Manon Blanc , Olivier Bournez

The $d$-dimensional pattern matching problem is to find an occurrence of a pattern of length $m \times \dots \times m$ within a text of length $n \times \dots \times n$, with $n \ge m$. This task models various problems in text and image…

Quantum Physics · Physics 2015-08-27 Ashley Montanaro

We present linear time {\it in-place} algorithms for several basic and fundamental graph problems including the well-known graph search methods (like depth-first search, breadth-first search, maximum cardinality search), connectivity…

Data Structures and Algorithms · Computer Science 2019-07-24 Sankardeep Chakraborty , Kunihiko Sadakane , Srinivasa Rao Satti

Optimization problems over permutation matrices appear widely in facility layout, chip design, scheduling, pattern recognition, computer vision, graph matching, etc. Since this problem is NP-hard due to the combinatorial nature of…

Optimization and Control · Mathematics 2016-09-01 Bo Jiang , Ya-Feng Liu , Zaiwen Wen

In the present work, we present a new discrete logarithm algorithm, in the same vein as in recent works by Joux, using an asymptotically more efficient descent approach. The main result gives a quasi-polynomial heuristic complexity for the…

Cryptography and Security · Computer Science 2013-11-27 Razvan Barbulescu , Pierrick Gaudry , Antoine Joux , Emmanuel Thomé

This paper narrows the gap between previous literature on quantum linear algebra and practical data analysis on a quantum computer, formalizing quantum procedures that speed-up the solution of eigenproblems for data representations in…

Quantum Physics · Physics 2022-08-09 Armando Bellante , Alessandro Luongo , Stefano Zanero

In this paper, we show $O(1.415^n)$-time and $O(1.190^n)$-space exact algorithms for 0-1 integer programs where constraints are linear equalities and coefficients are arbitrary real numbers. Our algorithms are quadratically faster than…

Data Structures and Algorithms · Computer Science 2014-11-04 Kenya Ueno

We present an efficient quantum algorithm aiming to find the negative curvature direction for escaping the saddle point, which is the critical subroutine for many second-order non-convex optimization algorithms. We prove that our algorithm…

Quantum Physics · Physics 2019-09-18 Kaining Zhang , Min-Hsiu Hsieh , Liu Liu , Dacheng Tao

We observe that any $T(n)$ time algorithm (quantum or classical) for several central linear algebraic problems, such as computing $\det(A)$, $tr(A^3)$, or $tr(A^{-1})$ for an $n \times n$ integer matrix $A$, yields a $O(T(n)) + \tilde…

Data Structures and Algorithms · Computer Science 2025-09-25 Kyle Doney , Cameron Musco

An adaptive regularization algorithm using high-order models is proposed for partially separable convexly constrained nonlinear optimization problems whose objective function contains non-Lipschitzian $\ell_q$-norm regularization terms for…

Optimization and Control · Mathematics 2021-05-31 Xiaojun Chen , Philippe Toint , Hong Wang

We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new class of accelerated first-order algorithms for constrained optimization. Unlike Frank-Wolfe or projected…

Optimization and Control · Mathematics 2025-05-02 Michael Muehlebach , Michael I. Jordan
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