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 31 for “"Asymptotic Optimality"”.
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Strongly Asymptotically Optimal Methods for the Pathwise Global Approximation of Stochastic Differential Equations with Coefficients of Super-linear Growth
… and we seek approximations that are strongly asymptotically optimal in specific classes of approximations. For the supremum error, we prove strong asymptotic optimality for specific tamed Euler schemes relating to certain adaptive and to equidistant time discretizations. For the L_p error, we …
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Optimal inventory control for assemble-to-order systems: A stochastic programming based asymptotic analysis framework
… a four-step Stochastic Programming (SP) based asymptotic analysis framework. The SP model, as a surrogate model to ATO systems, is easier to solve and can provide vital guidance in developing novel inventory control policies. And asymptotic analysis can be used to show that the inventory …
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Binary classification with training under both classes
… the two underlying probabilistic processes. Asymptotic optimality of binary hypothesis testing can be achieved with the knowledge of only one of the processes. It is also shown that the finite sample performance could improve greatly with additional knowledge of the alternate process. Most …
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INFORMED EXPLORATION ALGORITHMS FOR ROBOT MOTION PLANNING AND LEARNING
… this area endow these randomized planners with asymptotic optimality, their slow convergence rate still remains a challenge. One of the reasons for this poor performance can be traced to the widely used uniform sampling strategy that naively explores the entire search-space. Having access to an …
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Sampling-based algorithms for optimal path planning problems
… show that the existing algorithms either lack asymptotic optimality, i. e., almost-sure convergence to optimal solutions, or they lack computational efficiency: on one hand, neither the RRT nor the k-nearest PRM (for any fixed k) is asymptotically optimal; on the other hand, the simple PRM …
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On the information theory of clustering, registration, and blockchains
… its error exponent and prove its universal asymptotic optimality. We further extend this to design the max multiinformation method for universal multi-image registration and prove its universal asymptotic optimality. We then evaluate the non-asymptotic performance of image registration to …
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Some aspects of empirical likelihood
… chapters are also introduced.<br/>In chapter 3, Asymptotic Optimality of Empirical Likelihood Tests With Weakly Dependent Data, we extend the result of Kitamura (2001) to stationary mixing data. The key thing inproving the large deviation optimality is that the empirical measure of the …
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Coding for random access in wireless networks
… becomes imperative to understand the gap from optimality of the methods of random-access currently employed. In this thesis we discuss the trade-off between the required energy-per-bit to achieve a target probability of error (per-user) and the number of active users. Previous works in this …
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Image Segmentation and Robust Estimation Using Parzen Windows
… for the bandwidth (scale) of the window kernels. Asymptotic optimality of the proposed bandwidth is proved. The bandwidth selection scheme is validated for segmentation of real images. The density estimation framework is extended to model more structured images, e.g., those containing structures …
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A function space approach to the generalized nonlinear model with applications to frequency domain spectral estimation
… univariate time series which have the same asymptotic variance as those produced by maximizing the true likelihood. In this dissertation, McCullagh's theory is combined with a functional analysis approach and extended to parametric estimation of the spectral density matrix components of a …
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Optimal bandwidth selection rule for kernel regression estimator with dependent variables
… The main purpose of this work is to establish asymptotic optimality for a bandwidth selection rule under dependence which can be interpreted in terms of cross validation. In addition, some moment bounds for dependent variables will be established, which give more flexible bounds than existing …
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Asymptotically optimal path planning and surface reconstruction for inspection
… first problem, we develop a novel analysis of asymptotic optimality of control-space sampling path planning algorithms. This analysis demonstrated that asymptotically optimal path planning for any Lipschitz continuous dynamical system can be achieved by sampling the control space directly. We …
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Consensus-type stochastic approximation algorithms
<p>This work is concerned with asymptotic properties of consensus-type algorithms for networked systems whose topologies switch randomly. The regime-switching process is modeled as a discrete-time Markov chain with a nite state space. The consensus control is achieved by designing stochastic …
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Extrapolation and bandwidth choice in the regression discontinuity design
… algorithm produces a consistent estimator of the asymptotically optimal bandwidth and that the resulting regression discontinuity estimator satisfies the asymptotic optimality criterion of Li (1987). Finally, I provide Monte Carlo evidence suggesting that the proposed algorithm also performs well …
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Robust sampling-based motion planning for autonomous vehicles in uncertain environments
… by building upon RRT*, BU-RRT* is shown to be asymptotically optimal, enabling it to efficiently generate and optimize robust, dynamically feasible trajectories. For large and/or unbounded uncertainties, probabilistically feasible planning is provided through the proposed chance-constrained RRT …
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Scalable Estimation and Testing for Complex, High-Dimensional Data
… strong control of family-wise error rate and asymptotic optimality. Furthermore, appropriate compression in basis space leads to improved power as compared to point-wise testing in data domain or basis-space testing without compression. The effectiveness of the proposed procedure is …
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Sampling-based algorithms for stochastic optimal control
… We show that the iMDP algorithm guarantees asymptotic optimality while maintaining low computational and space complexity. In the second part of the thesis, we consider risk constraints that are expressed as either bounded trajectory performance or bounded probabilities of failure. For the …
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Essays on Decision Making Under Uncertainty
… We provide finite sample guarantees and prove asymptotic optimality for both methods. Computational experiments suggest that at least the second method overcomes a curse of dimensionality that afflicts existing methods, extrapolates better to unseen data, and achieves a many-fold decrease in …
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From data to decisions through new interfaces between optimization and statistics
… observations. We develop theory on tractability, asymptotic optimality, and performance metrics and apply our methods to leverage large-scale web data to drive a real-world inventory-management system. In the second half, we study the problem of data-driven pricing and show that a naive but common …
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Higher Order Asymptotics for the MSE of Robust M-Estimators of Location on Shrinking Total Variation Neighborhoods
… model, Rieder (1994) determines the optimal asymptotic linear estimator w.r.t. the asymptotic MSE evaluated uniformly on these neighbourhoods. We answer the question to which degree the asymptotic optimality carries over to finite sample size in the context of total variation neighbourhoods. …
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