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Projects and Research being conducted by the Center for Machine Learning and Applications.

  1. Manifold Learning from Unorganized High-dimensional Data Points (details)
  2. Matrix Algorithms for Data Clustering (details)
  3. Sufficient Dimension Reduction for High-dimensional Data with Applications in Bioinformatics (details)
  4. CAMLET: A Combined Ab-initio Manifold Learning Toolbox for Nanostructure Simulations (details)
  5. Tobacco Formula Funded Health Research (details)
  6. Efficient Computational Methods for Robust Multispectral Multiframe Superresolution (details)
  7. Software for Analyzing Biosequence Data (details)
  8. Large-scale Dynamic Meteorology: Cyclone structure characterization and evolution forecasting using cluster analysis and statistical-dynamical modeling
  9. Molecular dynamics in tumor cell extravasation (details)
  10. Neutrophil-mediated melanoma cell adhesion and migration (details)
  11. ITR: Computational Tools for Multicomponent Materials Design (details)
  12. Analysis, Algorithms and Computations for Model Problems in Material Science (details)
  13. Career: Model Selection for Semiparametric Regression Models in High-dimensional Modeling and its Oracle Properties (details)
  14. On Elastic Complex Fluids with Complex (details)
  15. Maximum entropy model learning for classification and more general inference tasks: large-scale applications and extensions (details)
  16. Collaborative research: testing and benchmarking methodologies for future network security mechanisms (details)
  17. A novel maximum entropy inference engine for data fusion in fault diagnosis


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