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 151 for “"high dimensionality"”.
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High dimensionality carrierless amplitude phase modulation technique for radio over fiber system
… one of the solutions to increase flexibility and high bit rates to support multi-level and multi-dimensional modulations with the absence of sinusoidal carrier. Recent work are focussing on the 2D CAP-64 QAM Radio-over-Fiber (RoF) system but no extension of higher dimensions is reported. This …
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Vision-based proprioception of a soft robotic finger with tactile sensing
… rigid-body counterparts. However, due to their high-dimensionality and flexibility, they still lack a quintessential human ability: the ability to accurately perceive themselves and the environment around them. To maximize their effectiveness, soft robots should be equipped with both …
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Beyond Limits: Detecting Anomalies in Sparse, High-dimensional Data
… of data-driven decision-making, particularly in high-stakes areas such as fraud detection and identifying manufacturing defects. However, the proprietary nature and specialized use cases of such data often result in data that is both high-dimensional and has limited samples. These challenges …
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Multi-sensor large scale land surface data assimilation using ensemble approaches
… land data assimilation problems results from the high dimensionality of states created by spatial discretization over large computational grids. The high dimensionality can be reduced by exploiting the fact that soil moisture field may have significant spatial correlation structure especially …
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Efficient visualization for large-scale and high-dimensional single-cell data
… visualization method for large-scale and high-dimensional single-cell data. Single-cell analysis can uncover the mysteries in the state of individual cells and enable us to construct new models of heterogeneous tissues. State-of-the-art technologies for single-cell analysis have been …
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High-dimensional machine learning for drug target discovery and precision medicine
… than the number of samples, which makes models highly likely to overfit the training data (high-dimensionality). Second, there are technical and/or experimental confounders in any one study that make the features learned from an individual expression dataset not necessarily generalizable to …
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Dynamic model for space-time weather radar observation and nowcasting
… in modeling spacetime radar observations: 1) high dimensionality due to the high-resolution radar measurements over a large area, 2) non-stationarity due to the storm motion, and 3) non-stationarity due to evolution (growth and decay). These difficulties are addressed in this research. To deal …
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
… can be attributed to its robustness to high dimensionality problem. However, when the high-dimensional data is a sparse one, RF procedures are inefficient. Thus, this thesis aims at improving the efficiency of RF by providing a probabilistic framework using Bayesian reasoning. The …
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Energy efficient accelerators for autonomous navigation in miniaturized robots
… in autonomous navigation systems because of the high dimensionality of the problem. For example, multi-scale object detection is desired for robustness, which requires significant data expansion. Additionally, a 3D map size grows overtime while the robot explores the environment, which requires …
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Prediction, analysis, and learning of advective transport in dynamic fluid flows
… exist, the inherent nonlinearities and the high dimensionality of complex fluid systems make it very challenging to develop the capabilities to accurately compute and characterize advective material transport. We systematically study the problems of predicting, uncovering, and learning the …
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Clustering and dimensionality reduction for time-series service monitoring data
… data to monitor their availability, therefore, high dimensionality, unlabeled data and changing data distribution are all prevalent. In this thesis, we efficiently address these three issues using the constructed service monitoring dataset. Higher dimensionality means higher computational cost …
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Extensible neural network software : applications in gene expression analysis
… life sciences for analysis of large data sets. High-throughput technologies, such as gene expression microarrays, have challenged traditional statistical learning algorithms given their high dimensionality. This thesis describes GAINN, a neural network software package I created. GAINN was …
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Adapting ADTrees for Improved Performance on Large Datasets with High Arity Features
… query time, particularly on datasets with very high dimensionality and with high arity features. We propose five modifications to the ADtree, each of which can be used to improve size and query time under specific types of datasets and features. These modifications also provide an increased …
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Learning to teach and meta-learning for sample-efficient multiagent reinforcement learning
… including the multiagent credit assignment, the high dimensionality of the problems, and the lack of convergence guarantees. As a result, many experiences are often required to learn effective multiagent policies. This thesis introduces two frameworks to reduce the sample complexity in MARL. The …
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A branching fuzzy-logic classifier for building optimization
… to emulate a complex building simulation of high dimensionality. Many multi-dimensional systems are dominated by the behavior of a small number of inputs over a limited range of input variation. Some also exhibit a tendency to respond relatively strongly to certain inputs over small ranges, …
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Projection methods for clustering and semi-supervised classification
… task. Projection methods are extremely useful in high dimensional applications, and situations in which the data contain irrelevant dimensions which can be counterinformative for the clustering task. The final contribution addresses high dimensionality in the context of a data stream. Data streams …
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On Adiabatic Quantum Molecular Dynamics
… solve and compute approximations for due to the highly oscillatory nature of the solutions in space and time and due to the high dimensionality of the state space. In the spirit of Born and Oppenheimer, we study quantitatively the approximation of the molecular evolution. We obtain an iterable …
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Approximation of prices for average-type options via bounds
… in closed-form and numerically because of the high dimensionality of the problem. In this thesis we develop methods that avoid these issues by providing price approximations in the form of lower and upper bounds. We do so by approximating the event that the option finishes in-the-money with a …
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EXTRACT NESSENTIAL FACTORS FROM HIGH DIMENSIONAL BIG DATA
… On the other hand, the massive sample size, high dimensionality and complex dependence of big data create computational and statistical challenges that cannot be handled by the conventional analytical methods. It turns out essential factors extracted from data are useful to explain the …
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Motion Planning for Manipulation With Heuristic Search
… commonly thought of as impractical due to the high-dimensionality of the planning problem. As part of this thesis work, we have developed a heuristic search-based approach to motion planning for manipulation that does deal effectively with the high-dimensionality of the problem. In this thesis, …
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