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 7 of 7 for “"Convex Analysis of Mixtures"”.
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Design and Implementation of Convex Analysis of Mixtures Software Suite
Various convex analysis of mixtures (CAM) based algorithms have been developed to address real world blind source separation (BSS) problems and proven to have good performances in previous papers. This thesis reported the implementation of a comprehensive software CAM-Java, which contains three …
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A Study of Machine Learning Approaches for Biomedical Signal Processing
The introduction of high-throughput molecular profiling technologies provides the capability of studying diverse biological systems at molecular level. However, due to various limitations of measurement instruments, data preprocessing is often required in biomedical research. Improper preprocessing …
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Unsupervised Signal Deconvolution for Multiscale Characterization of Tissue Heterogeneity
… complex tissues requires precise identification of distinctive cell types, cell-specific signatures, and subpopulation proportions. Tissue heterogeneity, arising from multiple cell types, is a major confounding factor in studying individual subpopulations and repopulation dynamics. Tissue …
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Mathematical Modeling and Deconvolution for Molecular Characterization of Tissue Heterogeneity
… subtypes, significantly obscures the analyses of molecular expression data derived from complex tissues. Existing computational methods performing data deconvolution from mixed subtype signals almost exclusively rely on supervising information, requiring subtype-specific markers, the number of …
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Machine Learning Approaches for Modeling and Correction of Confounding Effects in Complex Biological Data
With the huge volume of biological data generated by new technologies and the booming of new machine learning based analytical tools, we expect to advance life science and human health at an unprecedented pace. Unfortunately, there is a significant gap between the complex raw biological data from …
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Statistical Machine Learning for Multi-platform Biomedical Data Analysis
… and large-scale quantitative measurements of biomedical events. The need to analyze the produced vast amount of imaging and genomic data stimulates various novel applications of statistical machine learning methods in many areas of biomedical research. The main objective is to assist …
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Multi-Platform Molecular Data Integration and Disease Outcome Analysis
One of the most common measures of clinical outcomes is the survival time. Accurately linking cancer molecular profiling with survival outcome advances clinical management of cancer. However, existing survival analysis relies intensively on statistical evidence from a single level of data, without …