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Showing 1 to 7 of 7 for “"Fused Lasso"”.

  1. A Modern Statistical Approach to Quality Improvement in Health Care using Quantile Regression

    … regression technique that incorporates a fused-lasso-type penalty.

    ohiolink Repository record for A Modern Statistical Approach to Quality Improvement in Health Care using Quantile Regression (opens in a new tab)

  2. Inference of Gene Regulatory Networks with integration of prior knowledge

    … of the resulting networks. We extended the Fused Sparse Structural Equation Models (FSSEM) framework to create the Fused Lasso Adaptive Prior (FLAP) method. FSSEM incorporates gene expression data and genetic variants in the form of expression quantitative trait loci (eQTLs) perturbations. …

    trento Repository record for Inference of Gene Regulatory Networks with integration of prior knowledge (opens in a new tab)

  3. Exploiting sparsity for machine learning in big data

    … efficient algorithm based on sparsity-inducing fused lasso framework. Experiment results on various datasets show that our algorithm effectively smooths out noises and captures the real event, outperforming several state- of-the-art methods consistently in noisy setting. To sum up, this thesis …

    uiuc Repository record for Exploiting sparsity for machine learning in big data (opens in a new tab)

  4. Contributions to Structured Variable Selection Towards Enhancing Model Interpretation and Computation Efficiency

    … such as the best subset selection and the Lasso, often do not take the underlying data generation mechanism into considerations. This thesis proposal aims to develop statistical modeling methodologies with a focus on the structured variable selection towards better model interpretation and …

    vt Repository record for Contributions to Structured Variable Selection Towards Enhancing Model Interpretation and Computation Efficiency (opens in a new tab)

  5. Bayesian Variable Selection and Inference for Nonparametric Kernel Machine and Functional Models

    … method is developed under a generalized fused multi-kernel machine regression. This method can apply to continuous/binary/ordered categorical response variables. We demonstrate the advantage of our method using bio-photonics Raman spectroscopy to identify which molecular fingerprinting …

    vt Repository record for Bayesian Variable Selection and Inference for Nonparametric Kernel Machine and Functional Models (opens in a new tab)

  6. New progress in hot-spots detection, partial-differential-equation-based model identification and statistical computation

    … Least Absolute Shrinkage and Selection Operator (Lasso) type problem. In this thesis, we have four main works. Chapter 1 and Chapter 2 fall in the first area, i.e., hot-spots detection in spatio-temporal data. Chapter 3 belongs to the second area, i.e., PDE-based model identification. Chapter 4 is …

    gatech Repository record for New progress in hot-spots detection, partial-differential-equation-based model identification and statistical computation (opens in a new tab)

  7. Semiparametric and Nonparametric Methods for Complex Data

    A variety of complex data has broadened in many research fields such as epidemiology, genomics, and analytical chemistry with the development of science, technologies, and design scheme over the past few decades. For example, in epidemiology, the matched case-crossover study design is used to …

    vt Repository record for Semiparametric and Nonparametric Methods for Complex Data (opens in a new tab)