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 361 for “"optimization methods"”.
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Optimization methods for political redistricting
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01
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Optimization methods for dynamical systems learning
L'abstract è presente nell'allegato / the abstract is in the attachment
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Convex optimization methods for model reduction
Model reduction and convex optimization are prevalent in science and engineering applications. In this thesis, convex optimization solution techniques to three different model reduction problems are studied.Parameterized reduced order modeling is important for rapid design and optimization of …
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Integer optimization methods for machine learning
In this thesis, we propose new mixed integer optimization (MIO) methods to ad- dress problems in machine learning. The first part develops methods for supervised bipartite ranking, which arises in prioritization tasks in diverse domains such as information retrieval, recommender systems, natural …
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Optimization methods applied to containership design
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Naval Architecture and Marine Engineering, 1967.
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Optimization methods for active and passive localization
… sources themselves. This dissertation studies optimization methods for high precision active and passive localization. In the case of active localization, multiple transmit elements illuminate the targets from different directions. The signals emitted by the transmitters may differ in power and …
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COMBINATORIAL OPTIMIZATION METHODS FOR PROBLEMS IN GENOMICS
I recenti progressi in genomica hanno sollevato una miriade di problemi estremamente stimolanti dal punto di vista computazionale; in particolare, per molti di essi e' stata provata l'appartenenza alla classe dei problemi NP-hard. Sulla base di questi risultati, grande attenzione e' stata posta …
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Multifidelity optimization methods for interconnected multidisciplinary systems
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-08-01
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Large-Scale Optimization Methods: Theory and Applications
Large-scale optimization problems appear quite frequently in data science and machine learning applications. In this thesis, we show the efficiency of coordinate descent (CD) and mirror descent (MD) methods in solving large-scale optimization problems. First, we investigate the convergence rate of …
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Optimal Vehicle Path Generator Using Optimization Methods
… This study specifically concentrates on applying optimization concepts to generate paths that meet two separate objective functions; minimum time and maximum tire forces. A three-degree-of freedom vehicle model is used to approximate the handling dynamics of the vehicle. Inputs into the vehicle …
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Global optimization methods for localization in compressive sensing
… the intersection between signal processing and optimization. It advocates the sensing of "sparse" signals (i.e., represented using just a few terms from a basis expansion) by using a sampling rate much lower than that required by the Nyquist-Shannon sampling theorem (i.e., twice the highest …
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Reinforcement learning and optimization methods in sensor networks
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms
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Optimization Methods for Machine Learning under Structural Constraints
… reduction. In this thesis, we present scalable optimization methods for several large-scale machine learning problems under structural constraints, with a focus on shape constraints in nonparametric statistics and sparsity in high-dimensional statistics. In the first chapter, we consider the …
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Large-scale optimization Methods for data-science applications
… we present several contributions of large scale optimization methods with the applications in data science and machine learning. In the first part, we present new computational methods and associated computational guarantees for solving convex optimization problems using first-order methods. We …
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Convex optimization methods for graphs and statistical modeling
… approaches is the development of computational methods based on convex optimization, which are in turn useful in a broad array of problems in signal processing and machine learning. The specific contributions are as follows: -- We propose a convex optimization method for decomposing the sum of a …
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Resource management of cognitive radio networks with optimization methods.
… and dynamically adapts its transmission methods and the channel usage so that the induced interference to the licensed user is regulated. The dissertation focuses on solving three kinds of problems of the cognitive radio networks: (1) Multiple-input and multiple-output (MIMO) transmission …
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Water resources decision making using meta-heuristic optimization methods
… focus was to investigate meta-heuristic (global) optimization methods suitable for developing water resources decision support system (DSS), particularly to optimally design and operate groundwater storage and recovery projects. The effort included developing an integrated simulation-optimization …
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Optimization methods for topological design of interconnected ring networks
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Blast mitigation strategies for vehicles using shape optimization methods
This thesis is concerned with the study of blast effects on vehicular structures. The specific problem of a point source blast originating under the vehicle hull is considered, and its impact on the solid body is measured in terms of the total impulse acting on the vehicle. Simplified …
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