Embracing Uncertainty: The New Machine Learning

  • Chris Bishop
  • Published 2011 in
    2011 IEEE 35th Annual Computer Software and…

Abstract

Computers are based on logic, but must increasingly deal with real-world data that is full of uncertainty and ambiguity. Modern approaches to machine learning use probability theory to quantify and compute with this uncertainty, and have led to a proliferation in the applications of machine learning, ranging from recommendation systems to web search, and… (More)
DOI: 10.1109/COMPSAC.2011.118

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