Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 48 for “"distributed optimization"”.
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Distributed Optimization Algorithms for Networked Systems
<p>Distributed optimization methods allow us to decompose an optimization problem</p><p>into smaller, more manageable subproblems that are solved in parallel. For this</p><p>reason, they are widely used to solve large-scale problems arising in areas as diverse</p><p>as wireless communications, …
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Distributed optimization on a wireless sensor network testbed
The focus of this thesis is to implement various distributed optimization algorithms on a physical wireless sensor network. Distributed optimization refers to optimization of some global function which is not completely known to any single node in a communication network. The global function is …
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Distributed optimization and market analysis of networked systems
… problems in large-scale multi-agent convex optimization systems, which includes the LASSO (Least-Absolute Shrinkage and Selection Operator) and many other important machine learning problems. We propose fast fully distributed both synchronous and asynchronous ADMM (Alternating Direction …
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Communication efficient large scale distributed optimization with curvature acceleration
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01
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Distributed optimization with applications to sensor networks and machine learning
This dissertation deals with developing optimization algorithms which can be distributed over a network of computational nodes. Specifically we develop distributed algorithms for the special class when the optimization problem of interest has a separable structure. In this case the objective …
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Distributed optimization in multi-agent systems: applications to distributed regression
… of each agent. The focus of this thesis is distributed stochastic optimization in multi-agent systems. In distributed optimization, the complete optimization problem is not available at a single location but is distributed among different agents. The distributed optimization problem is …
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Distributed optimization of traffic delay on a periodic switched grid network
… decisions). Additionally, we present a distributed algorithm which makes use of messages passed between adjacent nodes to arrive at a solution with low delay, when compared with what is obtained when nodes take decisions independently. Furthermore, dealing with large networks proves …
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A proximal atomic coordination algorithm for distributed optimization in distribution grids
… methodologies, it has become imperative that new distributed control strategies are developed to better regulate the increasingly volatile nature of modern generation and load profiles. In this thesis, we introduce a distributed control strategy called Proximal Atomic Coordination (PAC) to solve …
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Asynchronous, distributed optimization for the coordinated planning of air and space assets
… both air and space assets in an asynchronous and distributed environment. We consider requests with time windows and priority levels, some of which require simultaneous observations by different sensors. We consider how these improvements could impact Earth observing sensors in two use areas; …
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Hypergraph Distributed Optimization & Decentralized Control with Applications in Economic Networks and Graphical Games
… the clique expansion graphs in the settings of distributed optimization and decentralized control. In both settings we present results where the use of hypergraphs provides a scalable and a decentralized way for consistently better convergence rate. Additionally hypergraphs provide a more …
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Generalizations of the Alternating Direction Method of Multipliers for Large-Scale and Distributed Optimization
… at solving many large-scale and structured optimization problems, particularly arising from the areas of compressive sensing, signal and image processing, machine learning and applied statistics. Moreover, the algorithm can be implemented in a fully parallel and distributed manner to process …
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Foundations of Multiple-Time-Scale Stochastic Approximation for Fast and Resilient Distributed Optimization Algorithms
… for analyzing and designing fast and resilient distributed optimization algorithms for large-scale networks. The central focus is on understanding and leveraging two-time-scale dynamics, which may arise naturally from the underlying network structure or be introduced through algorithmic design. …
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Optimal coordination of distributed energy resources in smart grids enabled by distributed optimization and transactive energy
… characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these DERs can only be achieved at the nexus of new technological approaches and policies, primarily distributed computation and transactive energy. …
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Gradient-Based Distributed Model Predictive Control
… model predictive control (MPC) and particularly distributed model predictive control (DMPC). One topic of the thesis is gradient-based optimization algorithms for solving the optimization problem arising in DMPC in a distributed manner. The underlying idea is to solve the optimization problem in …
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Accuracy-aware privacy mechanisms for distributed computation
"Distributed computing systems involve a network of devices or agents that use locally stored private information to solve a common problem. Distributed algorithms fundamentally require communication between devices leaving the system vulnerable to ""privacy attacks"" perpetrated by adversarial …
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Balancing information mixing and optimality: a framework for robust and efficient distributed decision-making
… scalability, and plug-and-play operation, distributed decision-making is becoming increasingly vital. This thesis develops a comprehensive framework to address the challenges in distributed decision-making, focusing on distributed optimization and control of multi-agent networks. It …
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Census-based population sutonomy for marine tobots: theory and experiments
… coupled with multi-objective behavior optimization for individual decision-making. The census component is expressed as a nonlinear opinion dynamics model and the multi-objective behavior optimization is accomplished using interval programming. This model can be reduced to recover …
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Census-Based Population Autonomy for Marine Robots: Theory and Experiments
… coupled with multi-objective behavior optimization for individual decision-making. The census component is expressed as a nonlinear opinion dynamics model and the multi-objective behavior optimization is accomplished using interval programming. This model can be reduced to recover …
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Cooperative communications in wireless networks : novel approaches in the mac layer
… to be simple, yet very efficient approach for distributed optimization and decision making in the cooperation problem. We show that the proposed MDP-based cooperation schemes and their extensions to reinforcement learning (RL) and partially observable MDP (POMDP) models are all able to …
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Generating Compact Wasp Nest Structures via Minimal Complexity Algorithms.
… knowledge can be applied to robotics and distributed optimization processes.</p>
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