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This paper studies two fundamental problems in power systems: the economic dispatch problem (EDP) and load shedding. For the EDP, an extension of the problem considering the transmission losses is presented. Because the optimization problem…

Systems and Control · Electrical Eng. & Systems 2021-08-31 Ismi Rosyiana Fitri , Jung-Su Kim

This paper considers a natural fault-tolerant shortest paths problem: for some constant integer $f$, given a directed weighted graph with no negative cycles and two fixed vertices $s$ and $t$, compute (either explicitly or implicitly) for…

Data Structures and Algorithms · Computer Science 2022-09-16 Virginia Vassilevska Williams , Eyob Woldeghebriel , Yinzhan Xu

In a previous paper I showed how the ideal SLAC derivative and second-derivative operators for an infinite lattice can be obtained in simple closed form in position space, and implemented very efficiently in a stochastic fashion for…

High Energy Physics - Lattice · Physics 2007-05-23 John P. Costella

A metro-line crossing minimization problem is to draw multiple lines on an underlying graph that models stations and rail tracks so that the number of crossings of lines becomes minimum. It has several variations by adding restrictions on…

Data Structures and Algorithms · Computer Science 2013-06-18 Yoshio Okamoto , Yuichi Tatsu , Yushi Uno

The discrete Fourier transform and the FFT algorithm are extended from the circle to continuous graphs with equal edge lengths.

Classical Analysis and ODEs · Mathematics 2008-08-18 Robert Carlson

Deep networks realize complex mappings that are often understood by their locally linear behavior at or around points of interest. For example, we use the derivative of the mapping with respect to its inputs for sensitivity analysis, or to…

Machine Learning · Computer Science 2019-07-09 Guang-He Lee , David Alvarez-Melis , Tommi S. Jaakkola

In this paper, we propose a class of matrix splitting-based fixed-point iteration (FPI) methods for solving the vertical nonlinear complementarity problem (VNCP). Under appropriate conditions, we present two convergence results obtained…

Optimization and Control · Mathematics 2025-01-15 Wang Yapeng , Mu Xuewen

Inverse problems consist of recovering a signal from a collection of noisy measurements. These problems can often be cast as feasibility problems; however, additional regularization is typically necessary to ensure accurate and stable…

Machine Learning · Computer Science 2021-04-30 Howard Heaton , Samy Wu Fung , Aviv Gibali , Wotao Yin

We propose a distributed algorithm based on Alternating Direction Method of Multipliers (ADMM) to minimize the sum of locally known convex functions using communication over a network. This optimization problem emerges in many applications…

Optimization and Control · Mathematics 2016-01-05 Ali Makhdoumi , Asuman Ozdaglar

Finding optimal matchings in dense graphs is of general interest and of particular importance in social, transportation and biological networks. While developing optimal solutions for various matching problems is important, the running…

Data Structures and Algorithms · Computer Science 2020-11-16 Nitish K. Panigrahy , Prithwish Basu , Don Towsley

This paper focuses on the distributed optimization of stochastic saddle point problems. The first part of the paper is devoted to lower bounds for the centralized and decentralized distributed methods for smooth (strongly) convex-(strongly)…

Machine Learning · Computer Science 2025-04-28 Aleksandr Beznosikov , Valentin Samokhin , Alexander Gasnikov

Distributed algorithms for solving coupled semidefinite programs (SDPs) commonly require many iterations to converge. They also put high computational demand on the computational agents. In this paper we show that in case the coupled…

Optimization and Control · Mathematics 2015-04-30 Sina Khoshfetrat Pakazad , Anders Hansson , Martin S. Andersen , Anders Rantzer

The problem of unsupervised learning node embeddings in graphs is one of the important directions in modern network science. In this work we propose a novel framework, which is aimed to find embeddings by \textit{discriminating…

Machine Learning · Statistics 2020-01-24 Stanislav Tsepa , Maxim Panov

We study offline change point localization and inference in dynamic multilayer random dot product graphs (D-MRDPGs), where at each time point, a multilayer network is observed with shared node latent positions and time-varying,…

Methodology · Statistics 2025-06-30 Fan Wang , Kyle Ritscher , Yik Lun Kei , Xin Ma , Oscar Hernan Madrid Padilla

Motivated by Pryce's structural index reduction method for differential algebraic equations (DAEs), we show the complexity of the fixed-point iteration algorithm and propose a fixed-point iteration method with parameters. It leads to a…

Numerical Analysis · Computer Science 2014-12-22 Juan Tang , Wenyuan Wu , Xiaolin Qin , Yong Feng

The problem of computing functions of values at the nodes in a network in a totally distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peer-to-peer,…

Networking and Internet Architecture · Computer Science 2007-05-23 Damon Mosk-Aoyama , Devavrat Shah

The aim of this paper is to analyze a class of consensus algorithms with finite-time or fixed-time convergence for dynamic networks formed by agents with first-order dynamics. In particular, in the analyzed class a single evaluation of a…

We present a new algorithm which is named the Dynamical Functional Particle Method, DFPM. It is based on the idea of formulating a finite dimensional damped dynamical system whose stationary points are the solution to the original…

Numerical Analysis · Mathematics 2013-03-25 Mårten Gulliksson , Sverker Edvardsson , Andreas Lind

In affine formation control problems, the construction of the framework with universal rigidity and affine localizability is a critical prerequisite, but it has not yet been well addressed, especially when additional agents join the…

Systems and Control · Electrical Eng. & Systems 2025-06-05 Huiming Li , Hao Chen , Xiangke Wang , Zhongkui Li , Lincheng Shen

This paper discusses a new method to solve definite integrals using artificial neural networks. The objective is to build a neural network that would be a novel alternative to pre-established numerical methods and with the help of a…

Machine Learning · Computer Science 2019-04-23 Satyasaran Changdar , Snehangshu Bhattacharjee
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