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 41 for “"ADMM"”.
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Efficient and Robust ADMM Methods for Dynamics and Geometry Optimization
We present novel ADMM-based methods for efficiently solving problems in a variety of applications in computer graphics. First, in the domain of physics-based animation we propose new techniques for simulating elastic bodies subject to dissipative forces. Second, in the field of geometry …
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ADMM Based Methods for Time-Domain Decomposition Formulations of Optimal Control Problems
… 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 memory intensive. TDD …
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Generalizations of the Alternating Direction Method of Multipliers for Large-Scale and Distributed Optimization
… The alternating direction method of multipliers (ADMM), as a versatile algorithmic tool, has proven to be very effective at solving many large-scale and structured optimization problems, particularly arising from the areas of compressive sensing, signal and image processing, machine learning and …
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Quantized Consensus by the Alternating Direction Method of Multipliers: Algorithms and Applications
… the alternating direction method of multipliers (ADMM) for networked applications, and in particular, consensus based detection in large scale sensor networks.</p> <p>We study the effects of two commonly used uniform quantization schemes, dithered and deterministic quantizations, on an ADMM based …
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Fast algorithm for joint unicast and multicast beamforming in large-scale systems
… 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 constraints. Utilizing the optimal multicast beamforming structure obtained …
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A proximal atomic coordination algorithm for distributed optimization in distribution grids
… PAC outperforms the standard distributed 2-Block ADMM algorithm, and we discuss the benefits of using PAC over 2-Block ADMM and other standard distributed solvers.
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Robust multi-group multicast beamforming design and antenna selection for massive MIMO systems
… 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 of antennas are available …
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Coordinated multicast beamforming for multi-cell massive MIMO systems
… 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. Following this, we consider the max-min fair …
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Communication-Aware, Scalable Gaussian Processes for Decentralized Exploration
… the alternating direction method of multipliers (ADMM). A closed-form solution of the decentralized proximal ADMM is provided for the case of GP hyper-parameter training with maximum likelihood estimation. Multiple aggregation techniques for GP prediction are decentralized with the use of …
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Large scale optimization for machine learning
… alternating direction method of multipliers (ADMM) provides a suitable framework for equality-constrained optimziation but raises some issues: (1) it does not provide a systematic way to solve subproblems; (2) it requires to solve all subproblems and synchronization; (3) it is a batch method …
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Cyber security threat modeling and experimental mitigation mechanisms in microgrids
… Alternating Direction Method of Multipliers (ADMM) algorithm for solving the decentralized control updates. The ADMM algorithm uses measurements at various points in the system to solve for control signals. Measurements and control commands are sent over communication networks such as …
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Decentralized Co-Optimization of Water and Energy Distribution Systems
… alternating direction method of multipliers (OB-ADMM) is also introduced to improve the distributed algorithm’s convergence and robustness for mixed-integer formulations, providing network participants with the same benefits that would be obtained with a centralized model, while also enjoying the …
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Constrained Matrix and Tensor Factorization: Theory, Algorithms, and Applications
… the alternating direction method of multipliers (ADMM): each matrix factor is updated in turn, using ADMM, hence the name AO-ADMM. This combination can naturally accommodate a great variety of constraints on the factor matrices, and almost all possible loss measures for the fitting. Computation …
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Tailoring Complexity of Model-Based Controllers for Legged Robots
… the alternating direction method of multipliers (ADMM) to provide low-accuracy solutions at high feedback rates. The controller is reliably deployed on hardware and enables the MIT Humanoid to walk robustly on rough terrains and plan complex crossed-leg and arm motions that enhance stability when …
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Distributed online algorithms for energy management in smart grids
… 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 coupled constraint that allows an abrupt change in power …
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Incentive mechanism design in blockchain-based federated learning over edge clouds
… the Alternating Direction Method of Multipliers (ADMM) is developed, ensuring convergence to a unique Nash equilibrium. This foundation is then extended to a more complex, three-tier cloud-edge-client Hierarchical Federated Learning (HFL) architecture. Here, a three-stage Stackelberg game is …
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Decentralized optimization approach for power distribution network and microgrid controls
… the alternating direction method of multipliers (ADMM) algorithm. The DVC design has simple node-to-node communication architecture while seamlessly adapting to dynamically varying system operating conditions and being robust against random communication link failures. To further reduce …
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Local differential privacy in decentralized optimization
… Alternating Direction Method of Multipliers (ADMM), and decentralized (stochastic) gradient descent(D(S)GD) as two concrete examples to propose a framework of first-order based optimization with random local aggregators. We prove such local randomization lead to the same utility guarantee but …
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Designing policy optimization algorithms for multi-agent reinforcement learning
… optimal power flow (ACOPF) problem solved via ADMM, with the goal of minimizing the number of iterations until convergence. Our method leads to significantly accelerated ADMM convergence compared to the state-of-the-art hand-designed parameter selection schemes and exhibits superior …
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Renewable Energy Integration in Distribution System with Artificial Intelligence
… The alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the reality of distribution systems, a three-phase unbalanced distribtion system is built, which consists of the hourly operation scheduling at substation level and …
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