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.
Results
Showing 1 to 20 of 39 for “"Alternating direction method of multipliers"”.
-
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 …
-
Generalizations of the Alternating Direction Method of Multipliers for Large-Scale and Distributed Optimization
… "Big Data", efficient and scalable computational methods are highly desirable to cope with the size of the data. 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 …
-
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 …
-
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 …
-
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 …
-
Tomographic reconstruction with adaptive sparsifying transforms
… in computed tomography (CT) is the reduction of harmful x-ray dose while maintaining the quality of reconstructed images. Methods which exploit the sparse representations of tomographic images have long been known to improve the quality of reconstructions from low-dose data. Recent work has …
-
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 …
-
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. …
-
Optimisation of Smart Grid performance using centralised and distributed control techniques
… Traditionally, power networks consisted of large power stations which were controlled from centralised locations. The trend in modern power networks is for generated power to be produced by a diverse array of energy sources which are spread over a large geographical area. As a result, …
-
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 …
-
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 …
-
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 …
-
Low rank methods for optimizing clustering
… models and problems in machine learning often have the majority of information in a low rank subspace. By careful exploitation of these low rank structures in clustering problems, we find new optimization approaches that reduce the memory and computational cost.</p> <p>We discuss two …
-
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 …
-
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 …
-
Analyzing intentions from big data traces of human activities
The rapid growth of big data formed by human activities makes research on intention analysis both challenging and rewarding. We study multifaceted problems in analyzing intentions from big data traces of human activities, and such problems span a range of machine learning, optimization, and …
-
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 …
-
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 …
-
Decentralized Co-Optimization of Water and Energy Distribution Systems
… the efficiency, resilience, and sustainability of both infrastructures. Traditional approaches manage electrical power and potable water networks independently, overlooking significant interdependencies between the two infrastructures that have an influence on operational costs, resource …
-
Power System State Estimation and Renewable Energy Optimization in Smart Grids
… bound on the estimation error, and propose a method for PMU placement in the grid. Using numerical examples, we show that by considering the phase angle mismatch in the measurements, the estimation accuracy can be significantly improved compared with the traditional weighted least-squares …
Page 1 of 2