Birs- 14w5086: Statistical and Computational Theory and Methodology for Big Data Analysis

  1. Title:
    Microbiome, Metagenomics and High-dimensional Compositional Data Analysis

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  2. Title:
    Tree-based Rare Variants Analyses

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  3. Title:
    When multi-core statistical computing fails for massive sample sizes

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  4. Title:
    A Split-and-Conquer Approach for Analysis of Extraordinarily Large Data

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  5. Title:
    BigData: Efficient Search and Learning using Sparse Random Projections and Probabilistic Hashing

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  6. Title:
    Uniform Ergodicity of the Iterated Conditional SMC and Geometric Ergodicity of Particle Gibbs Samplers

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  7. Title:
    On Nonparametric Profile Monitoring

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  8. Title:
    Functional Data Analysis of Imaging Data

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  9. Title:
    High-dimensional Inference in Magnetoencephalographic Neuroimaging

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  10. Title:
    Recent Developments of Iterative Monte Carlo Methods for Big Data Analysis (Faming Liang & Chuanhai Liu)

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  11. Title:
    Recent Software Development for Big Data Analysis

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  12. Title:
    Sparse and Low-Risk Regression in High Dimensions

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  13. Title:
    Quantile regression in Variable Screening

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  14. Title:
    What Is Beyond Sparse Coding?

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  15. Title:
    A Bayesian Approach to Subgroup Identification

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  16. Title:
    Detection of tumor driver genes using a fully integrated Bayesian approach

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  17. Title:
    Online Updating of Statistical Inference in the Big Data Setting

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  18. Title:
    Statistical Aggregation in Massive Data Environment

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  19. Title:
    Biocuration in the Era of Big Data

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  20. Title:
    Poly(A) motif Prediction Using Spectral Latent Features from Human DNA Sequences

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