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 29 for “"alternating direction method of multipliers (ADMM)"”.
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Distributed online algorithms for energy management in smart grids
… economic dispatch based on Subgradient method and Alternating Direction Method of Multipliers (ADMM), both designed to be agnostic with any initialization vector. The proposed distributed online solutions leverage a dynamic average consensus algorithm to track the time-variant linearly …
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Fast algorithm for joint unicast and multicast beamforming in large-scale systems
… (MIMO) system with a large number of unicast users. We propose an alternating direction method of multipliers (ADMM)-based fast algorithm that efficiently obtains the beamforming solutions for unicast and multicast users to minimize the transmit power subject to quality-of-service …
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ADMM Based Methods for Time-Domain Decomposition Formulations of Optimal Control Problems
This thesis investigates alternating direction method of multipliers (ADMM)-based methods for time-domain decomposition (TDD) formulations of linear-quadratic partial differential equation (PDE)-constrained optimization problems. The solution of such optimization problems is computing time and …
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Local differential privacy in decentralized optimization
… yet with industrial adoption, which allows data of an individual to be privatized before sharing. Consequently, more challenges are encountered to build efficient statistical analyzer in LDP setting. Towards practical decentralized optimization in LDP, we extend LDP into a more comprehensive …
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Coordinated multicast beamforming for multi-cell massive MIMO systems
… applicable to massive MIMO systems, we apply the alternating direction method of multipliers (ADMM) technique and propose an ADMM-based first-order algorithm to solve the quality of service (QoS) problem, which decompose the QoS problem into subproblems with closed/semi-closed form updates. …
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Communication-Aware, Scalable Gaussian Processes for Decentralized Exploration
… acoustic communication performance from a set of measurements. We compare kriging to cokriging with vehicle range as a secondary variable using a simple approximate linear-log model of the communication performance. Next, we propose a model-based learning methodology for the prediction of …
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Optimal electric vehicle charging management: coordination of multiple charging methods and technologies
… areas with huge populations and various types of charging demands. This dissertation initially reviews EV charging technologies and presents a new classification. Next, to address the EV charging management challenges, it investigates optimal EV charging management models and studies the …
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Architectures and algorithms for voltage control in power distribution systems
… the slow time-scale, in which the settings of conventional voltage regulation devices are adjusted, and the fast time-scale, in which voltage regulation through active/reactive power injection shaping is accomplished. Slow time-scale devices will generally be existing hardware, e.g., voltage …
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Coupled Natural Gas and Electric Power Systems
… natural gas networks. The intermittent operation of gas-fired plants to balance wind generation introduces spatiotemporal fluctuations of increasing gas demand. At the heart of modeling, monitoring, and control of gas networks is a set of nonlinear equations relating nodal gas injections and …
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Mathematical Optimization Algorithms for Model Compression and Adversarial Learning in Deep Neural Networks
… (DNNs) have made breakthroughs in a variety of tasks, such as image recognition, speech recognition and self-driving cars. However, their large model size and computational requirements add a significant burden to state-of-the-art computing systems. Weight pruning is an effective approach to …
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Robust multi-group multicast beamforming design and antenna selection for massive MIMO systems
In this dissertation, we use an Alternating Direction Method of Multipliers (ADMM) algorithm to design robust multi-group multicast beamforming scheme for massive multiple-input multiple-output (MIMO) systems for two scenarios; 1) all antennas are available at the base station (BS), 2) only subset …
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Successive convex approximation: analysis and applications
The block coordinate descent (BCD) method is widely used for minimizing a continuous function f of several block variables. At each iteration of this method, a single block of variables is optimized, while the remaining variables are held fixed. To ensure the convergence of the BCD method, the …
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Decentralized Baseband Processing for Massive MU-MIMO Systems
… for systems with hundreds or thousands of antennas and generates raw baseband data rates that exceed the limits of current interconnect technology and chip I/O interfaces. This thesis proposes novel decentralized baseband processing architectures that alleviate these bottlenecks by …
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Tailoring Complexity of Model-Based Controllers for Legged Robots
… human-like mobility, but must manage complex and often conflicting control objectives. While model-based controllers can address these challenges using online optimization, they have high computational demands. Model predictive control (MPC) provides closed-loop stability with online trajectory …
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Incentive mechanism design in blockchain-based federated learning over edge clouds
… bottlenecks, vulnerability to single points of failure, and a lack of transparency in model aggregation. While integrating blockchain technology into FL systems mitigates these security risks and ensures traceability, the resulting architecture demands significant computational and …
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Heterogeneity modeling and longitudinal clustering
… needs.In this thesis, we develop several types of methods and theory to accommodate heterogeneity modeling in various personalization applications for longitudinal data. In the first application, we propose a personalized drug dosage recommendation scheme. Specifically, we model patients' …
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Quantized Consensus by the Alternating Direction Method of Multipliers: Algorithms and Applications
… processing is a major tenet in the fields of control, signal processing, information theory, and computer science. Agents operating in a coordinated fashion can gain greater efficiency and operational capability than those perform solo missions. In many such applications the central task is …
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Trajectory planning under motion and sensing uncertainties: reachability analysis and connectivity maintenance
… applications such as transportation, delivery of goods, surveillance and cinematography. Additionally, multi-robot systems are being increasingly considered for applications such as exploration, target tracking and formation control. A vital component of these robotic systems is planning …
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Large scale optimization for machine learning
… bioinformatics to robotics. In entering the era of big data, large scale machine learning tools become increasingly important in training a big model on big data. Since machine learning problems are fundamentally empirical risk minimization problems, large scale optimization plays a key role in …
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Integration of electric vehicles into power systems
… impact on the reliability and sustainability of the power system. For instance, EV charging represents an intensive electric load. Their penetration into the power system poses significant challenges to the operation and control of the power distribution system. Therefore, grid operators need …
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