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The Tensor-Train (TT) format is a highly compact low-rank representation for high-dimensional tensors. TT is particularly useful when representing approximations to the solutions of certain types of parametrized partial differential…

We propose a hierarchical tensor-network approach for approximating high-dimensional probability density via empirical distribution. This leverages randomized singular value decomposition (SVD) techniques and involves solving linear…

Numerical Analysis · Mathematics 2026-01-13 Yifan Peng , Yian Chen , E. Miles Stoudenmire , Yuehaw Khoo

Many models for chaotic systems consist of joining two integrable systems with incompatible constants of motion. The quantum counterparts of such models have a propagator which factorizes into two integrable parts. Each part can be…

Chaotic Dynamics · Physics 2009-10-31 Tomaz Prosen , Thomas H. Seligman , Hans A. Weidenmueller

We propose algorithms for construction and random generation of hypergraphs without loops and with prescribed degree and dimension sequences. The objective is to provide a starting point for as well as an alternative to Markov chain Monte…

Data Structures and Algorithms · Computer Science 2020-04-14 Naheed Anjum Arafat , Debabrota Basu , Laurent Decreusefond , Stephane Bressan

We consider the problem of approximating a two-dimensional shape contour (or curve segment) using discrete assembly systems, which allow to build geometric structures based on limited sets of node and edge types subject to edge length and…

Computational Geometry · Computer Science 2021-02-03 Andreas M. Tillmann , Leif Kobbelt

A randomized algorithm for finding sparse cuts is given which is based on constructing a dual markov chain called multiscale rings process(MRP) and a new concept of entropy. It is shown how the time to absorption of the dual process…

Probability · Mathematics 2022-03-16 Farshad Noravesh

We introduce an algorithm to generate multivariate series of symbols from a finite alphabet with a given hierarchical structure of similarities. The target hierarchical structure of similarities is arbitrary, for instance the one obtained…

Computational Physics · Physics 2008-10-08 Mi. Tumminello , F. Lillo , R. N. Mantegna

We develop random graph models where graphs are generated by connecting not only pairs of vertices by edges but also larger subsets of vertices by copies of small atomic subgraphs of arbitrary topology. This allows the for the generation of…

Statistics Theory · Mathematics 2021-04-21 Anatol E. Wegner , Sofia Olhede

A qualitative comparison of total variation like penalties (total variation, Huber variant of total variation, total generalized variation, ...) is made in the context of global seismic tomography. Both penalized and constrained…

Geophysics · Physics 2012-04-09 Ignace Loris , Caroline Verhoeven

Randomized iterative algorithms have attracted much attention in recent years because they can approximately solve large-scale linear systems of equations without accessing the entire coefficient matrix. In this paper, we propose two novel…

Numerical Analysis · Mathematics 2021-10-22 Kui Du , Xiao-Hui Sun

Matrices with low-rank structure are ubiquitous in scientific computing. Choosing an appropriate rank is a key step in many computational algorithms that exploit low-rank structure. However, estimating the rank has been done largely in an…

Numerical Analysis · Mathematics 2024-01-08 Maike Meier , Yuji Nakatsukasa

Polynomial zonotopes, a non-convex set representation, have a wide range of applications from real-time motion planning and control in robotics, to reachability analysis of nonlinear systems and safety shielding in reinforcement learning.…

Systems and Control · Electrical Eng. & Systems 2023-05-19 Yushen Huang , Ertai Luo , Stanley Bak , Yifan Sun

The Expectation--Maximization (EM) algorithm is a simple meta-algorithm that has been used for many years as a methodology for statistical inference when there are missing measurements in the observed data or when the data is composed of…

Machine Learning · Statistics 2022-11-15 Hideitsu Hino , Shotaro Akaho , Noboru Murata

This paper proposes fast randomized algorithms for computing the Kronecker Tensor Decomposition (KTD). The proposed algorithms can decompose a given tensor into the KTD format much faster than the existing state-of-the-art algorithms. Our…

Numerical Analysis · Mathematics 2025-05-22 Salman Ahmadi-Asl , Naeim Rezaeian , Andre L. F. de Almeida , Yipeng Liu

A randomized algorithm for computing a data sparse representation of a given rank structured matrix $A$ (a.k.a. an $H$-matrix) is presented. The algorithm draws on the randomized singular value decomposition (RSVD), and operates under the…

Numerical Analysis · Mathematics 2024-06-25 James Levitt , Per-Gunnar Martinsson

Resampling is a standard step in particle filters and more generally sequential Monte Carlo methods. We present an algorithm, called chopthin, for resampling weighted particles. In contrast to standard resampling methods the algorithm does…

Computation · Statistics 2016-08-24 Axel Gandy , F. Din-Houn Lau

This paper presents a state-of-the-art algorithm for the vertex enumeration problem of arrangements, which is based on the proposed new pivot rule, called the Zero rule. The Zero rule possesses several desirable properties: i) It gets rid…

Combinatorics · Mathematics 2025-03-26 Zelin Dong , Fenglei Fan , Huan Xiong , Tieyong Zeng

Pretropisms are candidates for the leading exponents of Puiseux series that represent solutions of polynomial systems. To find pretropisms, we propose an exact gift wrapping algorithm to prune the tree of edges of a tuple of Newton…

Computational Geometry · Computer Science 2016-06-20 Jeff Sommars , Jan Verschelde

We show that a very simple randomised algorithm for numerical integration can produce a near optimal rate of convergence for integrals of functions in the $d$-dimensional weighted Korobov space. This algorithm uses a lattice rule with a…

Numerical Analysis · Mathematics 2023-04-21 Frances Y. Kuo , Dirk Nuyens , Laurence Wilkes

This paper presents a fast and simple new 2-approximation algorithm for minimum weighted vertex cover. The unweighted version of this algorithm is equivalent to a well-known greedy maximal independent set algorithm. We prove that this…

Data Structures and Algorithms · Computer Science 2022-09-13 Nate Veldt
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