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Motivated by robust matrix recovery problems such as Robust Principal Component Analysis, we consider a general optimization problem of minimizing a smooth and strongly convex loss function applied to the sum of two blocks of variables,…

Machine Learning · Computer Science 2019-11-19 Dan Garber , Shoham Sabach , Atara Kaplan

This Note revisits the Leibnitz integral calculus method based on differentiation under the integral sign with respect to a parameter either already existing or introduced ad hoc. Through several cases exemplifying the method, it is shown…

History and Overview · Mathematics 2023-08-21 Jean-Luc Boulnois

We present new pivot rules for the Simplex method for LPs over 0/1 polytopes. We show that the number of non-degenerate steps taken using these rules is strongly polynomial and even linear in the dimension or in the number of variables. Our…

Optimization and Control · Mathematics 2021-11-30 Alexander Black , Jesús De Loera , Sean Kafer , Laura Sanità

Although nearly 20 years have passed since its conception, the feasibility pump algorithm remains a widely used heuristic to find feasible primal solutions to mixed-integer linear problems. Many extensions of the initial algorithm have been…

Optimization and Control · Mathematics 2024-11-07 Matteo Cacciola , Alexandre Forel , Antonio Frangioni , Andrea Lodi

We introduce the smoothed analysis of algorithms, which is a hybrid of the worst-case and average-case analysis of algorithms. In smoothed analysis, we measure the maximum over inputs of the expected performance of an algorithm under small…

Data Structures and Algorithms · Computer Science 2009-09-25 Daniel A. Spielman , Shang-Hua Teng

In this paper, we analyze the simplex method with the largest distance rule and derive upper bounds on the number of different basic feasible solutions generated. The pivoting rule was proposed by Pan [10], and in some cases, it was…

Optimization and Control · Mathematics 2026-03-24 Tomonari Kitahara

Although it is relatively easy to apply, the gradient method often displays a disappointingly slow rate of convergence. Its convergence is specially based on the structure of the matrix of the algebraic linear system, and on the choice of…

Numerical Analysis · Mathematics 2025-06-03 Ibrahima Dione

Discovering "good" algorithms for an operation is often considered an art best left to experts. What if there is a simple methodology, an algorithm, for systematically deriving a family of algorithms as well as their cost analyses, so that…

Programming Languages · Computer Science 2018-08-24 Devangi N. Parikh , Margaret E. Myers , Richard Vuduc , Robert A. van de Geijn

We introduce innovative algorithms for computing exact or approximate (minimum-norm) solutions to $Ax=b$ or the {\it normal equation} $A^TAx=A^Tb$, where $A$ is an $m \times n$ real matrix of arbitrary rank. We present more efficient…

Numerical Analysis · Mathematics 2023-11-30 Bahman Kalantari

We present a novel iterative algorithm for approximating the linear least squares solution with low complexity. After a motivation of the algorithm we discuss the algorithm's properties including its complexity, and we present theoretical…

Data Structures and Algorithms · Computer Science 2016-11-15 Michael Lunglmayr , Christoph Unterrieder , Mario Huemer

A new numerical method for solving a scalar ordinary differential equation with a given initial condition is introduced. The method is using a numerical integration procedure for an equivalent integral equation and is called in this paper…

Numerical Analysis · Mathematics 2011-09-06 Alexander Lozovskiy

We describe and analyze a simple algorithm for sampling from the solution $\mathbf{x}^* := \mathbf{A}^+\mathbf{b}$ to a linear system $\mathbf{A}\mathbf{x} = \mathbf{b}$. We assume access to a sampler which allows us to draw indices…

Data Structures and Algorithms · Computer Science 2025-08-19 Tyler Chen , Junhyung Lyle Kim , Archan Ray , Shouvanik Chakrabarti , Dylan Herman , Niraj Kumar

The one way function based on the Collatz problem is proposed. It is based on the problem's conditional branching structure which is not considered as important even the 3x+1 question is quite famous. The analysis shows why the problem is…

Computational Complexity · Computer Science 2018-07-27 Rade Vuckovac

We show that a straightforward rewrite of a known minimal polynomial algorithm yields a simpler version of a recent algorithm of A. Salagean.

Information Theory · Computer Science 2016-11-17 Graham H. Norton

The chase procedure is a fundamental algorithmic tool in databases that allows us to reason with constraints, such as existential rules, with a plethora of applications. It takes as input a database and a set of constraints, and iteratively…

Databases · Computer Science 2023-03-24 Marco Calautti , Mostafa Milani , Andreas Pieris

In the present paper, a robust approach to a special class of convex feasibility problems is considered. By techniques of convex and variational analysis, conditions for the existence of robust feasible solutions and related error bounds…

Optimization and Control · Mathematics 2025-05-06 Amos Uderzo

Many scientifically well-motivated statistical models in natural, engineering and environmental sciences are specified through a generative process, but in some cases it may not be possible to write down a likelihood for these models…

Computation · Statistics 2018-10-10 Sanjay Chaudhuri , Subhro Ghosh , David J. Nott , Kim Cuc Pham

We present an astonishingly simple and elegant proof of the celebrated Basel problem.

Classical Analysis and ODEs · Mathematics 2025-06-16 Jesus Retamozo

Many proofs of the fundamental theorem of algebra rely on the fact that the minimum of the modulus of a complex polynomial over the complex plane is attained at some complex number. The proof then follows by arguing the minimum value is…

Numerical Analysis · Computer Science 2014-09-09 Bahman Kalantari

Recently, there has been a lot of interest in using neural networks for solving partial differential equations. A number of neural network-based partial differential equation solvers have been formulated which provide performances…

Machine Learning · Computer Science 2020-04-21 Shehryar Malik , Usman Anwar , Ali Ahmed , Alireza Aghasi