Multivariate Time Series and Social Media AnalysisInfering and understanding the structure and dynamics of large-scale, complex systems.
Nonparanormal modeling, graph-valued regression, Statistical Learning Theory with Dependent Data.
Genomics and Text MiningStructured Genome-Transcriptome-Phenome association analysis for complex diseases, gene context set analysis.
Batch effects modeling, reliable prediction, and robust biomarker detection.
Bio-imaging and Computational Cognitive NeuroscienceUnderstanding complex human behavior and brain.
Neural semantic basis discovery, fMRI and DCE-MRI data analysis, brain activity graph.
Viral Epidemics and Clinical TrialsPredicting the evolution of infectious diseases like Influenza.
Clinical trials and adaptive design, causal inference, MIDAS.
Statistics
Keywords: large-scale nonparametric inference.
Functional sparsity and structural sparsity; high dimensional nonparametric inference.
Optimization
Keywords: nonsmooth convex optimization.
Theory and algorithms of nonsmooth convex optimization and high performance computing.
Probability
Keywords: probabilistic modeling, dependent data.
Probabilistic graphical modeling; theory and methods for dependent data analysis
Statistical Machine Learning in Science and Engineering
Keywords: genomics, bio-imaging, text, epidemiology, informatics networks.
We develop statistical methods and easy-to-use softwares that address a wide variety of data analsyis problems, raning from genomics, cognitive neuroscience, to social media analysis.
Highlights
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The Nonparanormal SKEPTIC
Feb 10th, 2012 | Paper
Han Liu, Fang Han, Ming Yuan, John Lafferty, and Larry Wasserman