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We introduce a new and increasingly relevant setting for distributed optimization in machine learning, where the data defining the optimization are unevenly distributed over an extremely large number of nodes. The goal is to train a…

Machine Learning · Computer Science 2016-10-11 Jakub Konečný , H. Brendan McMahan , Daniel Ramage , Peter Richtárik

We establish stable finite element (FE) approximations of convection-diffusion initial boundary value problems using the automatic variationally stable finite element (AVS-FE) method. The transient convection-diffusion problem leads to…

Numerical Analysis · Mathematics 2024-01-08 Eirik Valseth , Pouria Behnoudfar , Clint Dawson , Albert Romkes

Distributed system applications rely on a fine-grain common sense of time. Existing systems maintain the common sense of time by keeping each independent machine as close as possible to wall-clock time through a combination of software…

Systems and Control · Electrical Eng. & Systems 2022-04-04 Sanjay Lall , Calin Cascaval , Martin Izzard , Tammo Spalink

In this paper, we present a distributed optimal multiagent control scheme for quadrotor formation tracking under localization errors. Our control architecture is based on a leader-follower approach, where a single leader quadrotor tracks a…

Systems and Control · Electrical Eng. & Systems 2023-01-31 Clinton Enwerem , John Baras , Danilo Romero

A novel autonomous chunk-based aerial additive manufacturing framework is presented, supported with experimental demonstration advancing aerial 3D printing. An optimization-based decomposition algorithm transforms structures into…

This paper considers a novel problem of how to choose an appropriate geometry for a group of agents with only shape constraints but with a flexible scale. Instead of assigning the formation system with a specific geometry, here the only…

Systems and Control · Computer Science 2015-03-18 Huang Huang , Changbin Yu , Qinghe Wu

This work considers the distance constrained formation control problem with an additional constraint requiring that the formation exhibits a specified spatial symmetry. We employ recent results from the theory of symmetry-forced rigidity to…

Optimization and Control · Mathematics 2025-01-29 Daniel Zelazo , Shin-ichi Tanigawa , Bernd Schulze

To facilitate widespread adoption of automated engineering design techniques, existing methods must become more efficient and generalizable. In the field of topology optimization, this requires the coupling of modern optimization methods…

Computational Engineering, Finance, and Science · Computer Science 2024-02-23 Connor N. Mallon , Aaron W. Thornton , Matthew R. Hill , Santiago Badia

This work introduces a distributed formation control strategy for multi-agent systems based solely on rotation symmetry constraints. We propose a potential function that enforces inter-agent \textbf{rotational} symmetries, whose gradient…

Systems and Control · Electrical Eng. & Systems 2026-03-12 Zamir Martinez , Daniel Zelazo

The problem of distributed controller synthesis for formation control of multi-agent systems is considered. The agents (single integrators) communicate over a communication graph and a decentralized linear feedback structure is assumed. One…

Optimization and Control · Mathematics 2013-05-17 Ameer K. Mulla , Rachel K. Kalaimani , Debraj Chakraborty , Madhu N. Belur

Motivated by control-affine systems in optimal control theory, we introduce the notion of a point-affine distribution on a manifold X - i.e., an affine distribution F together with a distinguished vector field contained in F. We compute…

Differential Geometry · Mathematics 2009-10-07 Jeanne N. Clelland , Christopher G. Moseley , George R. Wilkens

Structural topology optimization, which aims to find the optimal physical structure that maximizes mechanical performance, is vital in engineering design applications in aerospace, mechanical, and civil engineering. Generative adversarial…

Machine Learning · Computer Science 2022-12-07 François Mazé , Faez Ahmed

Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything (V2X) communication to share perceptual data, enhances detection but is vulnerable to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Xi Zhou , Tao Huang , Qing-Long Han , Rana Abbas , Mostafa Rahimi Azghadi

In the expanding field of machine learning, federated learning has emerged as a pivotal methodology for distributed data environments, ensuring privacy while leveraging decentralized data sources. However, the heterogeneity of client data…

Machine Learning · Computer Science 2025-01-28 Alice Smith , Bob Johnson , Michael Geller

In this paper we consider the problem of a multi-agent system achieving a formation in the presence of misbehaving or adversarial agents. We introduce a novel continuous time resilient controller to guarantee that normally behaving agents…

Systems and Control · Computer Science 2021-06-11 James Usevitch , Kunal Garg , Dimitra Panagou

Generally, the normal displacement-based formation control has a sensing mode that requires the agent not only to have certain knowledge of its direction, but also to gather its local information characterized by nonnegative coupling…

Optimization and Control · Mathematics 2023-06-06 Zhen Li , Yang Tang , Yongqing Fan , Tingwen Huang

3D printing techniques such as Fused Deposition Modeling (FDM) have enabled the fabrication of complex geometry quickly and cheaply. High stiffness parts are produced by filling the 2D polygons of consecutive layers with contour-parallel…

Graphics · Computer Science 2020-04-29 Tim Kuipers , Eugeni L. Doubrovski , Jun Wu , Charlie C. L. Wang

This paper studies the distributed control and estimation of multi-agent systems based on bearing information. In particular, we consider two problems: (i) the distributed control of bearing-constrained formations using relative position…

Systems and Control · Computer Science 2015-03-31 Shiyu Zhao , Daniel Zelazo

Federated Learning is a framework that jointly trains a model \textit{with} complete knowledge on a remotely placed centralized server, but \textit{without} the requirement of accessing the data stored in distributed machines. Some work…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-26 Jia Qian , Lars Kai Hansen , Xenofon Fafoutis , Prayag Tiwari , Hari Mohan Pandey

Decentralized optimization is widely used in large scale and privacy preserving machine learning and various distributed control and sensing systems. It is assumed that every agent in the network possesses a local objective function, and…

Optimization and Control · Mathematics 2023-01-31 Savelii Chezhegov , Anton Novitskii , Alexander Rogozin , Sergei Parsegov , Pavel Dvurechensky , Alexander Gasnikov