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 60 for “"Convergence analysis"”.
-
A Convergence Analysis of Generalized Hill Climbing Algorithms
… and tabu search. A necessary and a sufficient convergence condition for GHC algorithms are presented. The convergence conditions presented in this dissertation are based upon a new iteration classification scheme for GHC algorithms. The convergence theory for particular formulations of GHC …
-
Quantitative convergence analysis of dynamical processes in machine learning
This thesis focuses on analyzing the quantitative convergence of selected important machine learning processes, from a dynamical perspective, in order to understand and guide machine learning practices. Machine learning is becoming increasingly popular in various fields. Typical machine learning …
-
Classification with Large Sparse Datasets: Convergence Analysis and Scalable Algorithms
… need to be answered. 1. Sparse data and convergence behavior. How different properties of a dataset, such as the sparsity rate and the mechanism of missing data systematically affect convergence behavior of classification? 2. Handling sparse data with non-linear model. How to efficiently …
-
Convergence analysis of the generalized finite element method with global-local enrichments
Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by William Ingram (wingram2@illinois.edu) on 2010-08-31T20:04:56Z Item is restricted until 2012-08-31T20:04:44Z
-
Convergence Analysis of Heterogeneous Decision-making Populations Under the Coordinating Best-response and Imitation Update Rules
… parties. We studied the problem of equilibrium convergence in such games in both discrete and continuous (time) cases. In the first Chapter, we provide a brief introduction to the field of game theory. We discuss different categories of agents based on their levels of rationality and …
-
Feasibility optimality of periodwise static priority policies for a quality of service model in wireless networks and convergence analysis for an online recommendation system
… The second part of the thesis analyzes the convergence of an algorithm for the problem of learning with expert advice. At the present time, several web-based recommendation systems use votes from experts or other users to recommend objects to other customers. We apply the `learning from …
-
Quasi-Newton and Multigrid Methods for Semiconductor Device Simulation
… of this approximation is demonstrated. Sheikh's convergence analysis of Gummel's method and quasi-Newton methods is extended to a nonuniform mesh and the Bernoulli function discretization. It is proved that Gummel's method and the quasi-Newton methods for the scaled carrier densities and carrier …
-
The E² Bathe subspace iteration method
… method was proposed that accelerated the convergence of the basic method by replacing some of the iteration vectors with more effective turning vectors. In this thesis, we build upon this recent acceleration effort and further enrich the subspace of each iteration by replacing additional …
-
The Clarke Derivative and Set-Valued Mappings in the Numerical Optimization of Non-Smooth, Noisy Functions
In this work we present a new tool for the convergence analysis of numerical optimization methods. It is based on the concepts of the Clarke derivative and set-valued mappings. Our goal is to apply this tool to minimization problems with non-smooth and noisy objective functions. After deriving a …
-
Deep Learning-based Numerical Methods for Stochastic Partial Differential Equations and Applications
… Neumann boundary conditions. We also prove the convergence analysis of the proposed algorithms. The numerical results indicate that the performance of the algorithm is quite effective for solving the SPDEs, even in high-dimensional cases. The applications include various pricing problems under …
-
Multilevel-in-Time Methods for Optimal Control of PDEs and Training of Recurrent Neural Networks
… problems. This thesis also develops a convergence analysis for inexact stochastic gradient methods. These methods allow the use of small, randomly selected batches of training data during the optimization, and they allow biases in the gradient approximations. The analysis does not …
-
Navigation in an unfamiliar environment using signal intensity
… simple closed curves, i.e. topological circles. Convergence analysis and distance bounds are established for the presented approach. The algorithm is then experimentally verified using a differential drive robot and an infrared beacon.
-
Finite volume schemes for hyperbolic-parabolic systems : error estimates
… balance laws in multi-space dimension. <br>The convergence analysis for the scalar case is well developed, even though <br>not complete up to now. In contrast, very few is known for the case of systems. <br>Following the ideas of J.P. Vila and P. Villedieu on one side, and of C.Dafermos on the …
-
A study of the computation and convergence behavior of eigenvalue bounds for self-adjoint operators
The convergence rates for the method of Weinstein and a variant method of Aronszajn known as "truncation including the remainder" are derived in terms of the containment gaps between exact and approximating subspaces, using analytical techniques that arise in part in the convergence analysis of …
-
CONVERGENGE ANALYSIS ON SVD-BASED ALGORITHMS FOR TENSOR LOW RANK APPROXIMATIONS
… algorithms improve two factors simultaneously. Convergence analysis both for the generalized Rayleigh quotient and the iterates themselves is the main contribution of this thesis. In addition, we also study the convergence property of a general framework called alternating direction methods …
-
Locking-free discontinuous Galerkin methods for problems in elasticity, using linear and multilinear approximations
… providing a remedy for the problem, an existing convergence analysis for triangles is looked at for possible extension to the case of quadrilaterals. This highlights the need for a suitable interpolant for the error-splitting approach of the proof. To rectify the problem manifesting in the …
-
GDSVD: Scalable k-SVD via Gradient Descent
… and random initialization enjoys global linear convergence for generic setting. Our convergence analysis reveals that the gradient method has an attracting region, and within this attracting region, the method behaves like Heron’s method (a.k.a. the Babylonian method). Empirically, we validate …
-
Domain Decomposition Methods for Convection-Diffusion-Reaction Equations with Finite Volume Discretizations
… preconditioner for the FVEMs and pro- vide an convergence analysis. Numerical experiments are provided to demonstrate our theoretical results.
-
A General Framework of Large-Scale Convex Optimization Using Jensen Surrogates and Acceleration Techniques
… general treatment, we present non-asymptotic convergence analysis of this family of methods and the motivation behind developing accelerated variants. Moreover, we discuss widely used acceleration techniques for convex optimization and then investigate acceleration techniques that can be used …
-
Model-based control of spatially extended systems
… explanation of model-based control. A general convergence analysis is presented for the purpose of establishing the criteria necessary for successful control. We investigate model-based control analytically for several classes of partial differential equations and use computer simulations to …
Page 1 of 3