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 16 of 16 for “"Convex Combination"”.
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Adaptive Robust Control
… can be readily designed. We then implement a convex combination of these controllers, the parameters of which are tuned based on error measurements. Using this approach, we are able to provide absolute bounds on the ability to adaptively stabilize against unmodeled dynamics.
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On Connections Between Univalent Harmonic Functions, Symmetry Groups, and Minimal Surfaces
… to minimal surfaces. We then proceed to consider convex combination harmonic mappings of the form f=sf_1+(1-s) f_2 and give conditions on when f lifts to a one-parameter family of minimal surfaces via the Weierstrauss-Enneper representation formula. Finally, we demand two minimal surfaces M and M' …
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Linear Mixed Model Robust Regression
… regression techniques predict mean response as a convex combination of a parametric and a nonparametric model fit to the data. It is a semiparametric method by which incompletely or incorrectly specified parametric models can be improved through adding an appropriate amount of a nonparametric fit. …
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Data based predictive control: Application to water distribution networks
… and computational complexity reasons. Linear convex combination is a simple and strong tool in continuous domain and computational load associated with the constrained optimization problems generated by linear convex combination are relatively soft. This fact makes the proposed data based …
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On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control
… the barrier MPC controller can be written as a convex combination of pieces arising from the explicit MPC formulation, (2) bounding the Hessian of the barrier MPC as a function of the strength of the barrier function, and (3) presenting new results in both matrix and convex analysis for …
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Model Robust Regression Based on Generalized Estimating Equations
… regression (MRR) predicts mean response as a convex combination of a parametric and a nonparametric prediction. MRR is a semiparametric method by which an incompletely or an incorrectly specified parametric model can be improved through adding an appropriate amount of a nonparametric fit. The …
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High Resolution Time-Limiter Schemes for Conservation Laws
… improved stability is realized by taking local convex combination of a higher order oscillatory method (accurate mode) with a first order unconditionally TVD method (stable mode). The application of time-limiters, which detects the local smoothness, enables the self-adjusting switch between …
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Evaluation of Stability Boundaries in Power Systems
… equilibrium. If the stability domain contains a convex combination of the two points, the control will aid the system in moving towards the equilibrium. The second contribution of this thesis is through the development and implementation of a pseudo non-linear evaluation of a power system as it …
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Identifiability for latent class models
… are topic models, which model each document by a convex combination of a set of word-frequency vectors, known as topics. Although identifying such latent topics is of primary interest in many applications, it is well-known that the topic parameters are not identifiable. Prior work addressed this …
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Nondifferentiable optimization algorithms with application to solving Lagrangian dual problems
… direction of motion turns out to be a particular convex combination of two successive subgradients and we establish suitable convergence results. In the second part of this dissertation, we consider Lagrangian dual problems. Our motivation here is the inadequacy of the simplex method or even …
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Robust Control for Inter-area Oscillations
In order to reduce the detrimental effects of inter-area oscillations on system stability, it is possible to use Linear Matrix Inequalities (LMIs) to design a multi-objective state feedback. The LMI optimization finds a control law that stabilizes several contingencies simultaneously using a …
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Three essays on applied microeconomics
… on fatalities rates. Results show that (i) a convex combination of the states of IL, MA and TX provide a good (synthetic) “peer state” for NY when evaluating this specific policy and (ii) that imposing the ban lead to a decrease of about 9% in fatality rates. The past two decades has seen an …
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Reframing Cox Proportional Hazards Model for Big Data and Neural Networks
… framework to fit Cox regression models with a convex combination of $l_1$ (lasso) and $l_2$ (ridge regression) penalties, also known as the elastic-net penalty. In Chapter 4of the dissertation, we tackle a problem that is a bit different from the survival analysis we discussed above. In …
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Message passing algorithms - methods and applications
… of causal portfolio strategies and computing a convex combination of these according to a carefully designed distribution. Universal (sublinear regret) performance bounds for each of these portfolios show that the algorithms asymptotically achieve the wealth of the best strategy from the …
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Machine learning and combinatorial methods for discrete optimization problems
… and approximate second-stage costs using a convex piecewise linear surrogate model. This results in a mixed-integer program which can be solved very quickly even for large instances. For the online phase, we propose a greedy policy. Simulations show that our approach can reduce expected …
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Audio computing in the wild: frameworks for big data and small computers
… of the symptom that the usual manifold-ignorant convex combination models, such as from low-rank matrix decomposition or topic modeling, tend to result in ambiguous regions in the source-specific subspace defined by the dictionary items as the bases. For example, in those ambiguous regions, the …