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 9 of 9 for “"model approximation"”.
-
Modeling and estimation in Gaussian graphical models : maximum-entropy methods and walk-sum analysis
Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fields such as computer vision, image processing, and distributed sensor networks. In this thesis we study two central …
-
Solution of sign and complex action problems with cluster algorithms
Two kinds of models are considered which have a Boltzmann weight which is either not real or real but not positive and so standard Monte Carlo methods are not applicable. These sign or complex action problems are solved with the help of cluster algorithms. In each case improved estimators for the …
-
Projected equation and aggregation-based approximate dynamic programming methods for Tetris
… equation methods, the cost-to-go function approximation [phi]r is updated by simulation using one of several policy-updated algorithms such as LSTD([lambda]) [BB96], and LSPE(A) [B196]. Projected equation methods generally may not converge. We define a pseudometric of policies and view the …
-
Explaining machine learning predictions : rationales and effective modifications
Deep learning models have demonstrated unprecedented accuracy in wide-ranging tasks such as object and speech recognition. These models can outperform techniques traditionally used in credit risk modeling like logistic regression. However, deep learning models operate as black-boxes, which can …
-
Generating CAD Parametric Features Based on Topology Optimization Results
… design strategies where robust parametric CAD models are used to generate new designs and part-families of current designs, as well as the tooling and manufacturing procedures. However, due to its complexity, the optimal topology results are often discarded or recreated by hand into a CAD …
-
Improving Machine Learning Through Oracle Learning
… training directly on a set of data, a learning model is trained to approximate a given oracle's behavior on a set of data. This can be beneficial in situations where it is easier to obtain an oracle than it is to use it at application time. It is shown that oracle learning can be applied to more …
-
Power System Frequency Control and Stability Analysis With Increasing Renewable Energy Penetration Level
… be enhanced. Moreover, both nonlinear dynamic model and small-signal linearization of Virtual Synchronous Generator controlled inverter system are derived, and key system parameters are identified. By imitating the mathematical model of a synchronous generator, some undesirable features are …
-
Algorithms and complexity analyses for some combinational optimization problems
… main interest is in problems in the master-slave model. In this model, each machine is either a master machine or a slave machine. Each job is associated with a preprocessing task, a slave task and a postprocessing task that must be executed in this order. Each slave task has a dedicated slave …
-
Capacity Characterization of Multi-Hop Wireless Networks- A Cross Layer Approach
… proposed increasingly realistic interference models that aim to capture the physical characteristics of radio signals. Some of the commonly used simple models that capture radio interference are based on geometric disk-graphs. The simplicity of these models facilitate the development of …