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