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Independent Component Analysis (ICA) is a statistical tool that decomposes an observed random vector into components that are as statistically independent as possible. ICA over finite fields is a special case of ICA, in which both the…

Machine Learning · Statistics 2018-11-14 Amichai Painsky , Saharon Rosset , Meir Feder

In this paper, a new general decomposition theory inspired from modular graph decomposition is presented. Our main result shows that, within this general theory, most of the nice algorithmic tools developed for modular decomposition are…

Data Structures and Algorithms · Computer Science 2007-05-23 Binh Minh Bui Xuan , Michel Habib , Vincent Limouzy , Fabien De Montgolfier

We propose an algorithm for low rank matrix completion for matrices with binary entries which obtains explicit binary factors. Our algorithm, which we call TBMC (\emph{Tiling for Binary Matrix Completion}), gives interpretable output in the…

Numerical Analysis · Mathematics 2020-06-23 Melanie Beckerleg , Andrew Thompson

We introduce a relational approach to program synthesis. The key idea is to decompose synthesis tasks into simpler relational synthesis subtasks. Specifically, our representation decomposes a training input-output example into sets of input…

Artificial Intelligence · Computer Science 2025-06-11 Céline Hocquette , Andrew Cropper

We determine the decomposition numbers of the partition algebra when the characteristic of the ground field is zero or larger than the degree of the partition algebra. This will allow us to determine for which exact values of the parameter…

Representation Theory · Mathematics 2014-03-21 Armin Shalile

We introduce a backward stable algorithm for computing the CS decomposition of a partitioned $2n \times n$ matrix with orthonormal columns, or a rank-deficient partial isometry. The algorithm computes two $n \times n$ polar decompositions…

Numerical Analysis · Mathematics 2018-04-25 Evan S. Gawlik , Yuji Nakatsukasa , Brian D. Sutton

Existing results on decomposition methods and algorithms for nonconvex problems are minimal. Parallel decomposition algorithms do not exist for nonconvex problems with coupling nonlinear equality constraints. Besides, decomposition…

Optimization and Control · Mathematics 2026-05-18 Yiqing Zhai , Ying Cui , Danny H. K. Tsang

We analyze the bit complexity of efficient algorithms for fundamental optimization problems, such as linear regression, $p$-norm regression, and linear programming (LP). State-of-the-art algorithms are iterative, and in terms of the number…

Data Structures and Algorithms · Computer Science 2023-04-06 Mehrdad Ghadiri , Richard Peng , Santosh S. Vempala

Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data analysis and scientific computing. This work surveys and extends recent research which…

Numerical Analysis · Mathematics 2014-04-29 Nathan Halko , Per-Gunnar Martinsson , Joel A. Tropp

A large number of computational and scientific methods commonly require decomposing a sparse matrix into triangular factors as LU decomposition. A common problem faced during this decomposition is that even though the given matrix may be…

Machine Learning · Computer Science 2023-10-17 Arpan Dasgupta , Pawan Kumar

Learning complex programs through inductive logic programming (ILP) remains a formidable challenge. Existing higher-order enabled ILP systems show improved accuracy and learning performance, though remain hampered by the limitations of the…

Artificial Intelligence · Computer Science 2022-08-02 Stanisław J. Purgał , David M. Cerna , Cezary Kaliszyk

Results are expoundd for the investigation of efficiency of the critical-component method for solving degenerate and ill-posed systems of linear algebraic equations

Rings and Algebras · Mathematics 2025-10-20 G. A. Emel'yanenko , M. G. Emelianenko , T. T. Rakhmonov , E. B. Dushanov , G. Yu. Konovalova

Decomposition techniques for linear programming are difficult to extend to conic optimization problems with general non-polyhedral convex cones because the conic inequalities introduce an additional nonlinear coupling between the variables.…

Optimization and Control · Mathematics 2013-06-04 Yifan Sun , Martin S. Andersen , Lieven Vandenberghe

In this paper we relate different formulations of the DPLL(T) procedure. The first formulation is based on a system of rewrite rules, which we denote DPLL(T). The second formulation is an inference system of, which we denote LKDPLL(T). The…

Logic in Computer Science · Computer Science 2012-04-24 Mahfuza Farooque , Stéphane Lengrand , Assia Mahboubi

This paper has been superseded by math.AG/0510287 and withdrawn by the author.

Algebraic Geometry · Mathematics 2007-05-23 V. Golyshev

A monolithic process is a single recursive equation with data parameters, which only uses non-determinism, action prefixing, and recursion. We present a technique that decomposes such a monolithic process into multiple processes where each…

Logic in Computer Science · Computer Science 2021-10-04 Maurice Laveaux , Tim A. C. Willemse

A saturation algorithm for collapsible pushdown systems was published in ICALP 2012. This work introduced a class of stack automata used to recognised regular sets of collapsible pushdown configurations. It was shown that these automata…

Formal Languages and Automata Theory · Computer Science 2018-05-31 Christopher Broadbent , Arnaud Carayol , Matthew Hague , Olivier Serre

In [7, Papadima and Suciu, When does the associated graded Lie algebra of an arrangement group decompose? Comment. Math. Helv. {\bf 81:4} (2006), 859--875] it is proved that the holonomy Lie algebra of an arrangement of hyperplanes through…

Rings and Algebras · Mathematics 2020-10-27 Clas Löfwall

Permutation decoding gained recent interest as it can exploit the symmetries of a code in a parallel fashion. Moreover, it has been shown that by viewing permuted polar codes as polar subcodes, the set of usable permutations in permutation…

Information Theory · Computer Science 2022-05-16 Marvin Geiselhart , Ahmed Elkelesh , Jannis Clausius , Stephan ten Brink

We propose a general proximal algorithm for the inversion of ill-conditioned matrices. This algorithm is based on a variational characterization of pseudo-inverses. We show that a particular instance of it (with constant regularization…

Numerical Analysis · Mathematics 2009-04-07 Pierre Maréchal , Aude Rondepierre
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