Unifying Modern Approaches in Machine Learning

  • Williamson, Robert (PI)
  • Schoelkopf, Bernhard (CoI)
  • Smola, Alexander J (CoI)

    Project: Research

    Project Details

    Description

    Bioinformatics and sensor networks are just two application areas that generate vast amounts of data for which sophisticated machine learning algorithms are needed to turn the data into useful knowledge. This proposal will integrate several very powerful approaches within machine learning to create improved tools that can better extract useful information from data. We will study kernel methods (an area in which the investigators are world experts), graphical models (which can be used to model complex causal dependences) and theoretical approaches to fully exploit the data available regardless of its quality. Outputs will include better machine learning algorithms usable for many problems such as detecting genetic influences on disease.
    StatusFinished
    Effective start/end date1/01/0731/12/11

    Fingerprint

    Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.