JPL Technical Report Server

Browsing by Subject "machine learning hypothesis ranking hypothesis selection incomplete information learning stochastic alternatives"

Browsing by Subject "machine learning hypothesis ranking hypothesis selection incomplete information learning stochastic alternatives"

Sort by: Order: Results:

  • Chien, S.; Stechert, A.; Mutz, D. (1999-06)
    This paper considers the problem of learning the ranking of a set of stochastic alternatives based upon incomplete information (i.e., a limited number of samples).