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A structural time series model additively decomposes into generative, semantically-meaningful components, each of which depends on a vector of parameters. We demonstrate that considering each generative component together with its vector of…

Methodology · Statistics 2020-09-16 David Rushing Dewhurst

Tandem duplication is an evolutionary process whereby a segment of DNA is replicated and proximally inserted. The different configurations that can arise from this process give rise to some interesting combinatorial questions. Firstly, we…

Combinatorics · Mathematics 2016-11-25 L Penso-Dolfin , CD Greenman

The Building Block Hypothesis (BBH) states that adaptive systems combine good partial solutions (so-called building blocks) to find increasingly better solutions. It is thought that Genetic Algorithms (GAs) implement the BBH. However, for…

Neural and Evolutionary Computing · Computer Science 2017-05-15 Jack McKay Fletcher , Thomas Wennekers

Generative models hold the promise of significantly expediting the materials design process when compared to traditional human-guided or rule-based methodologies. However, effectively generating high-quality periodic structures of materials…

Materials Science · Physics 2024-08-15 Anshuman Sinha , Shuyi Jia , Victor Fung

We examine the following version of a classic combinatorial search problem introduced by R\'enyi: Given a finite set $X$ of $n$ elements we want to identify an unknown subset $Y \subset X$ of exactly $d$ elements by testing, by as few as…

Combinatorics · Mathematics 2015-09-02 Fabrício S. Benevides , Dániel Gerbner , Cory T. Palmer , Dominik K. Vu

Graphical models are powerful tools for modeling high-dimensional data, but learning graphical models in the presence of latent variables is well-known to be difficult. In this work we give new results for learning Restricted Boltzmann…

Machine Learning · Computer Science 2020-07-28 Surbhi Goel , Adam Klivans , Frederic Koehler

The problem of finding a nontrivial factor of a polynomial f(x) over a finite field F_q has many known efficient, but randomized, algorithms. The deterministic complexity of this problem is a famous open question even assuming the…

Computational Complexity · Computer Science 2019-02-20 Manuel Arora , Gábor Ivanyos , Marek Karpinski , Nitin Saxena

We derive computationally tractable methods to select a small subset of experiment settings from a large pool of given design points. The primary focus is on linear regression models, while the technique extends to generalized linear models…

Machine Learning · Statistics 2017-12-21 Yining Wang , Adams Wei Yu , Aarti Singh

We define some new sequences of recursively constructed random combinatorial trees, and show that, after properly rescaling graph distance and equipping the trees with the uniform measure on vertices, each sequence converges almost surely…

Probability · Mathematics 2016-11-07 Nathan Ross , Yuting Wen

In this paper we propose a notion of pattern avoidance in binary trees that generalizes the avoidance of contiguous tree patterns studied by Rowland and non-contiguous tree patterns studied by Dairyko, Pudwell, Tyner, and Wynn.…

Discrete Mathematics · Computer Science 2024-06-17 Petr Gregor , Torsten Mütze , Namrata

Discrete structures are currently second-class in differentiable programming. Since functions over discrete structures lack overt derivatives, differentiable programs do not differentiate through them and limit where they can be used. For…

Programming Languages · Computer Science 2025-11-20 Joey Velez-Ginorio , Nada Amin , Konrad Kording , Steve Zdancewic

We consider the iterative solution of large linear systems of equations in which the coefficient matrix is the sum of two terms, a sparse matrix $A$ and a possibly dense, rank deficient matrix of the form $\gamma UU^T$, where $\gamma > 0$…

Numerical Analysis · Mathematics 2022-11-08 Michele Benzi , Chiara Faccio

Matrix completion aims to predict missing elements in a partially observed data matrix which in typical applications, such as collaborative filtering, is large and extremely sparsely observed. A standard solution is matrix factorization,…

Machine Learning · Computer Science 2019-08-06 Xiangju Qin , Paul Blomstedt , Samuel Kaski

We consider a stack sorting algorithm where only the appropriate output values are popped from the stack and then any remaining entries in the stack are run through the stack in reverse order. We identify the basis for the $2$-reverse pass…

Combinatorics · Mathematics 2018-08-14 Toufik Mansour , Howard Skogman , Rebecca Smith

The identification of repeating patterns in discrete grids is rudimentary within symbolic reasoning, algorithm synthesis and structural optimization across diverse computational domains. Although statistical approaches targeting noisy data…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Sushish Baral , Paulo Garcia , Warisa Sritriratanarak

Unsupervised machine learning via a restricted Boltzmann machine is an useful tool in distinguishing an ordered phase from a disordered phase. Here we study its application on the two-dimensional Ashkin-Teller model, which features a…

Disordered Systems and Neural Networks · Physics 2018-04-03 Wen-Jia Rao , Zhenyu Li , Qiong Zhu , Mingxing Luo , Xin Wan

A new probabilistic technique for establishing the existence of certain regular combinatorial structures has been recentlyintroduced by Kuperberg, Lovett, and Peled (STOC 2012). Using this technique, it can be shown that under certain…

Combinatorics · Mathematics 2020-07-02 Shachar Lovett , Sankeerth Rao , Alexander Vardy

This paper studies the Craig variant of the Golub-Kahan bidiagonalization algorithm as an iterative solver for linear systems with saddle point structure. Such symmetric indefinite systems in 2x2 block form arise in many applications, but…

Computational Engineering, Finance, and Science · Computer Science 2018-08-24 Mario Arioli , Carola Kruse , Ulrich Ruede , Nicolas Tardieu

Given a full column rank matrix $A \in \mathbb{R}^{m\times n}$ ($m\geq n$), we consider a special class of linear systems of the form $A^\top Ax=A^\top b+c$ with $x, c \in \mathbb{R}^{n}$ and $b \in \mathbb{R}^{m}$. The occurrence of $c$ in…

Numerical Analysis · Mathematics 2019-11-04 Henri Calandra , Serge Gratton , Elisa Riccietti , Xavier Vasseur

A general Boltzmann machine with continuous visible and discrete integer valued hidden states is introduced. Under mild assumptions about the connection matrices, the probability density function of the visible units can be solved for…

Machine Learning · Statistics 2020-01-29 Daniel Krefl , Stefano Carrazza , Babak Haghighat , Jens Kahlen