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In previous work, we demonstrated how decoding of a non-binary linear code could be formulated as a linear-programming problem. In this paper, we study different polytopes for use with linear-programming decoding, and show that for many…

Information Theory · Computer Science 2016-11-18 Vitaly Skachek , Mark F. Flanagan , Eimear Byrne , Marcus Greferath

Randomized algorithms provide solutions to two ubiquitous problems: (1) the distributed calculation of a principal component analysis or singular value decomposition of a highly rectangular matrix, and (2) the distributed calculation of a…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-09 Huamin Li , Yuval Kluger , Mark Tygert

Extreme classification problems are multiclass and multilabel classification problems where the number of outputs is so large that straightforward strategies are neither statistically nor computationally viable. One strategy for dealing…

Machine Learning · Statistics 2016-02-05 Paul Mineiro , Nikos Karampatziakis

Quantum algorithms are a very promising field. However, creating and manipulating these kind of algorithms is a very complex task, specially for software engineers used to work at higher abstraction levels. The work presented here is part…

We present here algorithms for efficient computation of linear algebra problems over finite fields.

Symbolic Computation · Computer Science 2013-05-21 Jean-Guillaume Dumas , Clément Pernet

We consider the primal problem of finding the zeros of the sum of a maximally monotone operator with the composition of another maximally monotone operator with a linear continuous operator and a corresponding dual problem formulated by…

Optimization and Control · Mathematics 2012-06-27 Radu Ioan Bot , Ernö Robert Csetnek , Andre Heinrich

We investigate the computational complexity of several basic linear algebra primitives, including largest eigenvector computation and linear regression, in the computational model that allows access to the data via a matrix-vector product…

Machine Learning · Computer Science 2021-05-25 Mark Braverman , Elad Hazan , Max Simchowitz , Blake Woodworth

This paper studies first-order algorithms for solving fully composite optimization problems over convex and compact sets. We leverage the structure of the objective by handling its differentiable and non-differentiable components…

Optimization and Control · Mathematics 2023-07-13 Maria-Luiza Vladarean , Nikita Doikov , Martin Jaggi , Nicolas Flammarion

New iterative methods for solving linear equations are presented that are easy to use, generalize good existing methods, and appear to be faster. The new algorithms mix two kinds of linear recurrence formulas. Older methods have either high…

Numerical Analysis · Mathematics 2012-03-13 Joseph F. Grcar

The linear ordering problem (LOP), which consists in ordering M objects from their pairwise comparisons, is commonly applied in many areas of research. While efforts have been made to devise efficient LOP algorithms, verification of whether…

Machine Learning · Computer Science 2023-05-23 Leszek Szczecinski , Harsh Sukheja

Counting the solution number of combinational optimization problems is an important topic in the study of computational complexity, especially on the #P-complete complexity class. In this paper, we first investigate some organizations of…

Computational Complexity · Computer Science 2015-06-19 Wei Wei , Renquan Zhang , Baolong Niu , Binghui Guo , Zhiming Zheng

This paper presents fast first-order methods for solving linear programs (LPs) approximately. We adapt online linear programming algorithms to offline LPs and obtain algorithms that avoid any matrix multiplication. We also introduce a…

Optimization and Control · Mathematics 2024-11-07 Wenzhi Gao , Dongdong Ge , Chunlin Sun , Yinyu Ye

The encoding of solutions in black-box optimization is a delicate, handcrafted balance between expressiveness and domain knowledge -- between exploring a wide variety of solutions, and ensuring that those solutions are useful. Our main…

Neural and Evolutionary Computing · Computer Science 2020-07-07 Adam Gaier , Alexander Asteroth , Jean-Baptiste Mouret

We give an algorithm for completing an order-$m$ symmetric low-rank tensor from its multilinear entries in time roughly proportional to the number of tensor entries. We apply our tensor completion algorithm to the problem of learning…

Data Structures and Algorithms · Computer Science 2015-11-25 Tselil Schramm , Benjamin Weitz

A conditional sampling oracle for a probability distribution D returns samples from the conditional distribution of D restricted to a specified subset of the domain. A recent line of work (Chakraborty et al. 2013 and Cannone et al. 2014)…

Data Structures and Algorithms · Computer Science 2016-08-18 Themistoklis Gouleakis , Christos Tzamos , Manolis Zampetakis

The {\em line sum optimization problem} asks for a $(0,1)$-matrix minimizing the sum of given functions evaluated at its row and column sums. We show that the {\em uniform} problem, with identical row functions and identical column…

Optimization and Control · Mathematics 2021-04-28 Martin Koutecky , Shmuel Onn

A numerical irreducible decomposition for a polynomial system provides representations for the irreducible factors of all positive dimensional solution sets of the system, separated from its isolated solutions. Homotopy continuation methods…

Mathematical Software · Computer Science 2018-06-19 Jan Verschelde

In this paper, given a linear system of equations A x = b, we are finding locations in the plane to place objects such that sending waves from the source points and gathering them at the receiving points solves that linear system of…

Numerical Analysis · Mathematics 2021-02-16 Kthim Imeri

Polynomial systems occur in many areas of science and engineering. Unlike general nonlinear systems, the algebraic structure enables to compute all solutions of a polynomial system. We describe our massive parallel predictor-corrector…

Mathematical Software · Computer Science 2015-05-05 Jan Verschelde , Xiangcheng Yu

We consider the problem of solving a large-scale system of linear equations in a distributed or federated manner by a taskmaster and a set of machines, each possessing a subset of the equations. We provide a comprehensive comparison of two…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-24 Boris Velasevic , Rohit Parasnis , Christopher G. Brinton , Navid Azizan