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Standard Gaussian Process (GP) regression, a powerful machine learning tool, is computationally expensive when it is applied to large datasets, and potentially inaccurate when data points are sparsely distributed in a high-dimensional…

Machine Learning · Computer Science 2016-03-08 Z. Zhang , K. Duraisamy , N. A. Gumerov

In this paper, a new method for solving the power flow problem in distribution systems which is fast, parallel, as well as modular, straightforward, simplified and generic is proposed. This approach is based on a hierarchical construction…

Systems and Control · Electrical Eng. & Systems 2023-09-06 Arbel Yaniv , Yuval Beck

An algorithm for the generation of shuttling sequences is necessary for the operation of a linear segmented ion-trap quantum computer. The present work provides an implementation of an algorithm that produces sequences proved to be optimal…

We address the problem of scheduling jobs with non-identical sizes and distinct processing times on a single batch processing machine, aiming at minimizing the makespan. The extensive literature on this NP-hard problem mostly focuses on…

Optimization and Control · Mathematics 2021-06-03 Renan Spencer Trindade , Olinto C. B. de Araujo , Marcia Fampa

We consider different online algorithms for a generalized scheduling problem for parallel machines, described in details in the first section. This problem is the generalization of the classical parallel machine scheduling problem, when the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-10 Istvan Szalkai , Gyorgy Dosa

This article deals with Part family formation problem which is believed to be moderately complicated to be solved in polynomial time in the vicinity of Group Technology (GT). In the past literature researchers investigated that the part…

Artificial Intelligence · Computer Science 2011-05-12 Tamal Ghosh , Mousumi Modak , Pranab K Dan

A scalable graphical method is presented for selecting, and partitioning datasets for the training phase of a classification task. For the heuristic, a clustering algorithm is required to get its computation cost in a reasonable proportion…

Machine Learning · Computer Science 2019-07-25 Sumedh Yadav , Mathis Bode

State-of-the-art data flow systems such as TensorFlow impose iterative calculations on large graphs that need to be partitioned on heterogeneous devices such as CPUs, GPUs, and TPUs. However, partitioning can not be viewed in isolation.…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-07 Ruben Mayer , Christian Mayer , Larissa Laich

We consider the problem of scheduling arrivals to a congestion system with a finite number of users having identical deterministic demand sizes. The congestion is of the processor sharing type in the sense that all users in the system at…

Optimization and Control · Mathematics 2017-04-12 Liron Ravner , Yoni Nazarathy

Large-scale parallel numerical simulations are essential for a wide range of engineering problems that involve complex, coupled physical processes interacting across a broad range of spatial and temporal scales. The data structures involved…

Mathematical Software · Computer Science 2018-10-11 Fande Kong , Roy H. Stogner , Derek R. Gaston , John W. Peterson , Cody J. Permann , Andrew E. Slaughter , Richard C. Martineau

The subject of this paper is the evolution of the concept of information processing in regular structures based on multi-level processing in nested cellular automata. The essence of the proposed model is a discrete space-time containing…

Neural and Evolutionary Computing · Computer Science 2022-10-13 Jerzy Szynka

Quantum circuits are typically represented by a (ordered) sequence of gates over a set of virtual qubits. During compilation, the virtual qubits of the gates are assigned to the physical qubits of the underlying quantum hardware, a step…

Fleets of networked manufacturing machines of the same type, that are collocated or geographically distributed, are growing in popularity. An excellent example is the rise of 3D printing farms, which consist of multiple networked 3D…

In this paper we consider the operator mapping problem for in-network stream processing applications. In-network stream processing consists in applying a tree of operators in steady-state to multiple data objects that are continually…

Distributed, Parallel, and Cluster Computing · Computer Science 2008-07-11 Anne Benoit , Henri Casanova , Veronika Rehn-Sonigo , Yves Robert

Multi-region segmentation algorithms often have the onus of incorporating complex anatomical knowledge representing spatial or geometric relationships between objects, and general-purpose methods of addressing this knowledge in an…

Computer Vision and Pattern Recognition · Computer Science 2014-06-09 John S. H. Baxter , Martin Rajchl , Jing Yuan , Terry M. Peters

This paper considers the scheduling of job families on parallel machines with time constraints on machine qualifications. In this problem, each job belongs to a family and a family can only be executed on a subset of qualified machines. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-17 Arnaud Malapert , Margaux Nattaf

Grouping the nodes of a graph into clusters is a standard technique for studying networks. We study a problem where we are given a directed network and are asked to partition the graph into a sequence of coherent groups. We assume that…

Social and Information Networks · Computer Science 2025-12-08 Iiro Kumpulainen , Nikolaj Tatti

The crew rostering problem (CRP) for pilots is a complex crew scheduling task assigning pairings, or sequences of flights starting and ending at the same airport, to pilots to create a monthly schedule. In this paper, we propose an…

Optimization and Control · Mathematics 2025-03-04 Philippe Racette , Frédéric Quesnel , Andrea Lodi , François Soumis

Since high data volume and complex data formats delivered in modern high-end production environments go beyond the scope of classical process control systems, more advanced tools involving machine learning are required to reliably recognize…

Machine Learning · Computer Science 2022-04-04 Stefan Schrunner , Michael Scheiber , Anna Jenul , Anja Zernig , Andre Kästner , Roman Kern

Reducing the fuel consumption within a power network is crucial to enhance the overall system efficiency and minimize operating costs. Fuel consumption minimization can be achieved through different optimization techniques where the output…

Optimization and Control · Mathematics 2023-10-30 Md Isfakul Anam , Tuyen Vu