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 151 for “"Minimax"”.
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Minimax Controller Design
Made available in DSpace on 2014-12-08T22:24:20Z (GMT). No. of bitstreams: 1 6808211.pdf: 2652815 bytes, checksum: d04c68f8a104d03749ebf93dd02fc765 (MD5) Previous issue date: 1967
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A Gradient Algorithm for Minimax Design
Made available in DSpace on 2014-12-08T22:24:37Z (GMT). No. of bitstreams: 1 7000872.pdf: 1008293 bytes, checksum: 260c870d28137831cc6a42b76b7b14b4 (MD5) Previous issue date: 1969
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Optimization and Generalization of Minimax Algorithms
This thesis explores minimax formulations of machine learning and multi-agent learning problems, focusing on algorithmic optimization and generalization performance. The first part of the thesis delves into the smooth convex-concave minimax problem, providing a unified analysis of widely used …
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Estimation of KL divergence: optimal minimax rate
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms
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Control of delay systems for minimax sensitivity
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 1986
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A Minimax Approach for Learning Gaussian Mixtures
… Training for Gaussian Mixture Models (GATGMM), a minimax GAN framework for learning GMMs. Motivated by optimal transport theory, we design the zero-sum game in GAT-GMM using a random linear generator and a softmax-based quadratic discriminator architecture, which leads to a non-convex concave …
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Sparse functional regression models: minimax rates and contamination
… in estimating the sensitive point. The minimax rate of convergence for estimating the parameters in sparse functional linear regression is derived. It is shown that the optimal rate for estimating the sensitive point depends on the roughness of the predictor function, which is quantified …
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Minimax Solution of Statistical Decision Problems by Iteration
Made available in DSpace on 2014-12-10T16:39:48Z (GMT). No. of bitstreams: 1 6604253.pdf: 1644729 bytes, checksum: 80509ed779017c294dbbc563de1c57e7 (MD5) Previous issue date: 1965
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Local versus global tables in Minimax Game Search
Minimax Game Search with alpha-beta pruning can utilize heuristic tables in order to prune more branches and achieve better performance. The tables can be implemented using different memory models: global tables, worker-local tables and processor-local tables. Depending on whether each heuristic …
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The Minimax control chart for multivariate quality control
… For this reason the chart has been named the Minimax control chart. A method for calculating probabilities for the joint distribution of Z<sub>[1]</sub> and Z<sub>[p]</sub> is developed. This method is used to determine the position of the four control limits of the chart; the upper and lower …
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Novel first-order methods for bilevel and minimax optimization.
Bilevel and minimax optimization problems arise in various fields, including machine learning, game theory, and decision science. This thesis highlights the underlying connections between constrained minimax and bilevel optimization and develops novel first-order methods with strong theoretical …
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A Unified Robust Minimax Framework for Regularized Learning Problems
… model. In this work, we propose a robust minimax formulation to interpret the relationship between data and regularization terms for a large class of loss functions. We show that various regularization terms are essentially corresponding to different distortions to the original data …
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Generalized Polynomial H(infinity) Predictive Control Utilizing Minimax Prediction
… of many H$\sb\infty$ controllers. The new minimax predictive minimization which uses a minimax predictor incorporates several time-honored control concepts as integral components of the control algorithm, so that satisfaction of time and frequency domain design specifications by the control …
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Exact Solution of Bayes and Minimax Change-Detection Problems
The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with …
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Admissible and Minimax Estimates of Parameters in Truncated Spaces
Made available in DSpace on 2014-12-05T22:27:21Z (GMT). No. of bitstreams: 1 6000200.pdf: 1228113 bytes, checksum: 75ba48f2772232c80ba87d9ade253ff7 (MD5) Previous issue date: 1959
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Exact Solution of Bayes and Minimax Change-Detection Problems
… problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes …
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Minimax sampling for key agreement generation in body sensor networks
… power. In this research, we have proposed minimax sampling during key agreement generation to optimize memory usage in body sensor network nodes. The experimental approach involved the use of Matlab toolkit and mathematical analysis. The signal was analysed using uniform sampling at 1Hz, …
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A Performance Analysis of the Minimax Multivariate Quality Control Chart
A performance analysis of three different Minimax control charts is performed with respect to their Chi-Square control chart counterparts under several different conditions. A unique control chart must be constructed for each process described by a unique combination of quality characteristic mean …
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Certain Minimax-Estimators of the Mean of a Multivariate Normal-Distribution
Made available in DSpace on 2014-12-11T18:24:08Z (GMT). No. of bitstreams: 1 7414519.pdf: 1525731 bytes, checksum: 4f6f5910ae08845bb0e832b5e7304960 (MD5) Previous issue date: 1974
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Design of minimax controllers for nonlinear systems using cost-to-come methods
… cost-to-come methodology for the construction of minimax controllers for nonlinear systems with partial-state information (PSI), which are subjected to deterministic uncertainty. It introduces the notion of a cost-to-come function and shows how it leads to necessary and sufficient conditions for …
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