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 12 of 12 for “"Support Vectors"”.
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Self-organising locally interpolating maps in control engineering
… and interpretably maps from a grid of input support vectors, e.g. a robot's velocity, to a grid of output support vectors, e.g. corresponding control commands. Moreover, a learning algorithm has been developed, which iteratively adapts the output support vectors such that the SOLIM map …
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Offline and online SVM performance analysis
… performance of a machine learning algorithm, the Support Vector Machine, this thesis compares the strengths and weaknesses between the offline and online SVM. The work includes the performance comparisons of SVMLight and LaSVM, with results of training time, number of support vectors, kernel …
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A statistical learning framework for data mining of large-scale systems : algorithms, implementation, and applications
A machine learning framework is presented that supports data mining and statistical modeling of systems that are monitored by large-scale sensor networks. The proposed algorithm is novel in that it takes both observations and domain knowledge into consideration and provides a mechanism that …
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Below P vs NP : fine-grained hardness for big data problems
… for empirical risk minimization such as kernel support vectors machines and other kernel machine learning problems. All of these problems have polynomial time algorithms, but despite extensive amount of research, no near-linear time algorithms have been found. We show that, under a natural …
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Eye detection using discriminatory features and an efficient support vector machine
… discriminatory features and a new efficient Support Vector Machine (eSVM). This dissertation first introduces five popular image representation methods - the gray-scale image representation, the color image representation, the 2D Haar wavelet image representation, the Histograms of Oriented …
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Support Vector Machine algorithms : analysis and applications
Support Vector Machines (SVMs) have attracted recent attention as a learning technique to attack classification problems. The goal of my thesis work is to improve computational algorithms as well as the mathematical understanding of SVMs, so that they can be easily applied to real problems. SVMs …
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Improved geo-referencing and prescreening for detection of buried explosive hazards in forward-looking infrared imagery
… inside the detection window. The feature vectors are classified using a SVM. This detector is compared to an existing prescreening algorithm that uses an ensemble of local RX anomaly detection filters trained via genetic algorithm. The proposed approach is shown to perform better across …
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Image segmentation and pattern classification using support vector machines
… method in input and feature spaces using Support Vector Machines (SVMs) is developed. In the input space, a subset of input features is selected by the ranking of their contributions to the decision function. In the feature space, features are ranked according to the weighted support …
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Comparison and performance enhancement of modern pattern classifiers
… also include performance uncertainties. Using support vector machine (SVM) as classification architectures, the thesis explores two potential enhancements to complexity reduction: (a) subset selection on the training data by some pre-processing approaches, and (b) organising the classes of a …
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Supervised Machine Learning Under Test-Time Resource Constraints: A Trade-off Between Accuracy and Cost
… of transforming data instances to feature vectors, and could be highly variable when features are heterogeneous. The latter reflects the effort of evaluating a classifier, which could be substantial, in particular nonparametric algorithms. We then propose three strategies to explicitly …
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Robust boosting via convex optimization
… herausgestellt - insbesondere Boosting und Support-Vektor-Maschinen. Ein großer Margin impliziert eine hohe Vorhersagequalität der Entscheidungsregel. Deshalb wird analysiert, wie groß der Margin bei Boosting ist und ein verbesserter Algorithmus vorgeschlagen, der effizient Regeln mit …
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Methodologies for remaining useful life estimation with multiple sensors in rotating machinery
… i) Proportional Hazards Μodel (PHM), ii) ε- Support Vector Regression ε-SVR and iii) Exponential extrapolation based on bootstrap sampling. In the current thesis a feature extraction scheme for prognosis is proposed and assessed based on time domain, frequency domain statistical features and …