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Data structures for efficient sampling from a set of weighted items are an important building block of many applications. However, few parallel solutions are known. We close many of these gaps both for shared-memory and distributed-memory…

数据结构与算法 · 计算机科学 2021-07-20 Lorenz Hübschle-Schneider , Peter Sanders

Upcoming HPC clusters will feature hybrid memories and storage devices per compute node. In this work, we propose to use the MPI one-sided communication model and MPI windows as unique interface for programming memory and storage. We…

分布式、并行与集群计算 · 计算机科学 2018-10-10 Sergio Rivas-Gomez , Roberto Gioiosa , Ivy Bo Peng , Gokcen Kestor , Sai Narasimhamurthy , Erwin Laure , Stefano Markidis

In this work we consider Bayesian inference problems with intractable likelihood functions. We present a method to compute an approximate of the posterior with a limited number of model simulations. The method features an inverse Gaussian…

统计计算 · 统计学 2021-02-23 Hongqiao Wang , Ziqiao Ao , Tengchao Yu , Jinglai Li

We survey results of a quarter century of work on computation by reversible general-purpose computers (in this setting Turing machines), and general reversible simulation of irreversible computations, with respect to energy-, time- and…

计算复杂性 · 计算机科学 2007-05-23 Paul Vitanyi

Computer power is a constantly increasing demand in scientific data analyses, in particular when Markov Chain Monte Carlo (MCMC) methods are involved, for example for estimating integral functions or Bayesian posterior probabilities. In…

分布式、并行与集群计算 · 计算机科学 2023-10-09 Fabio Castagna , Alberto Trombetta , Marco Landoni , Stefano Andreon

Within the field of multilinear algebra, inverses and generalized inverses of tensors based on the Einstein product have been investigated over the past few years. In this paper, we explore the singular value decomposition and full-rank…

数值分析 · 数学 2021-03-09 Ratikanta Behera , Sandip Maji , R. N. Mohapatra

We describe how to apply adjoint sensitivity methods to backward Monte-Carlo schemes arising from simulations of particles passing through matter. Relying on this, we demonstrate derivative based techniques for solving inverse problems for…

计算物理 · 物理学 2022-05-11 Roland Grinis

Data-driven inverse optimization for mixed-integer linear programs (MILPs), which seeks to learn an objective function and constraints consistent with observed decisions, is important for building accurate mathematical models in a variety…

最优化与控制 · 数学 2026-02-17 Akira Kitaoka

Modern, large scale monitoring systems have to process and store vast amounts of log data in near real-time. At query time the systems have to find relevant logs based on the content of the log message using support structures that can…

信息检索 · 计算机科学 2024-03-28 Julian Reichinger , Thomas Krismayer , Jan Rellermeyer

This paper presents an inverted-file k-means clustering algorithm (IVF) suitable for a large-scale sparse data set with potentially numerous classes. Given such a data set, IVF efficiently works at high-speed and with low memory…

机器学习 · 统计学 2020-02-24 Kazuo Aoyama , Kazumi Saito , Tetsuo Ikeda

With the surge of multi- and manycores, much research has focused on algorithms for mapping and scheduling on these complex platforms. Large classes of these algorithms face scalability problems. This is why diverse methods are commonly…

分布式、并行与集群计算 · 计算机科学 2017-07-27 Andrés Goens , Sergio Siccha , Jeronimo Castrillon

Solving inverse problems with Physics-Informed Neural Networks (PINNs) is computationally expensive for multi-query scenarios, as each new set of observed data requires a new, expensive training procedure. We present Inverse-Parameter Basis…

机器学习 · 计算机科学 2025-09-10 Shalev Manor , Mohammad Kohandel

This paper gives new, efficient algorithms for approximate uniform sampling of contingency tables and integer partitions. The algorithms use the Burnside process, a general algorithm for sampling a uniform orbit of a finite group acting on…

统计计算 · 统计学 2025-09-03 Persi Diaconis , Michael Howes

This paper introduces a computationally efficient algorithm in system theory for solving inverse problems governed by linear partial differential equations (PDEs). We model solutions of linear PDEs using Gaussian processes with priors…

机器学习 · 统计学 2025-06-16 Xin Li , Markus Lange-Hegermann , Bogdan Raiţă

A new runtime environment for the execution of recursive matrix algorithms on a supercomputer with distributed memory is proposed. It is designed both for dense and sparse matrices. The environment ensures decentralized control of the…

符号计算 · 计算机科学 2023-03-21 Gennadi Malaschonok , Alla Sidko

We consider the problem of private linear computation (PLC) in a distributed storage system. In PLC, a user wishes to compute a linear combination of $f$ messages stored in noncolluding databases while revealing no information about the…

信息论 · 计算机科学 2021-06-29 Sarah A. Obead , Hsuan-Yin Lin , Eirik Rosnes , Jörg Kliewer

We present several algorithms aimed at constructing sparse and structured sparse (row-sparse) generalized inverses, with application to the efficient computation of least-squares solutions, for inconsistent systems of linear equations, in…

最优化与控制 · 数学 2025-07-09 Gabriel Ponte , Marcia Fampa , Jon Lee , Luze Xu

The core-EP and BT inverses for rectangular matrices were studied recently in the literature. The main aim of this paper is to unify both concepts by means of a new kind of generalized inverse called $W$-weighted $q$-BT inverse. We analyze…

环与代数 · 数学 2024-03-22 D. E. Ferreyra , N. Thome , C. Torigino

In the paper we consider models of generalized counting processes time-changed by a general inverse subordinator, we characterize their distributions and present governing equations for them. The equations are given in terms of the…

概率论 · 数学 2023-12-11 Khrystyna Buchak , Lyudmyla Sakhno

Recently, physical layer (PHY) caching has been proposed to exploit the dynamic side information induced by caches at base stations (BSs) to support Coordinated Multi-Point (CoMP) and achieve huge degrees of freedom (DoF) gains. Due to the…

信息论 · 计算机科学 2018-10-18 An Liu , Vincent Lau , Wenchao Ding , Edmund Yeh
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