Now showing items 1-5 of 6

  • Bridge lane direction specifications for sustainable traffic management

    Foulds, James Richard; Foulds, Les R. (World Scientific Publishing, 2006)
    We present a deterministic model that specifies lane direction in a multi-laned bridge that has a movable barrier that divides the two directions of traffic flow, in order to reduce congestion. A probabilistic dynamic ...
  • Learning Instance Weights in Multi-Instance Learning

    Foulds, James Richard (The University of Waikato, 2008)
    Multi-instance (MI) learning is a variant of supervised machine learning, where each learning example contains a bag of instances instead of just a single feature vector. MI learning has applications in areas such as drug ...
  • A probabilistic dynamic programming model of rape seed harvesting

    Foulds, James Richard; Foulds, Les R. (Inderscience, 2006)
    We discuss a practical scenario from an operations scheduling viewpoint involving commercial contracting enterprises that visit farms in order to harvest rape seed crops. We report on a probabilistic dynamic programming ...
  • A review of multi-instance learning assumptions

    Foulds, James Richard; Frank, Eibe (Cambridge University Press, 2010)
    Multi-instance (MI) learning is a variant of inductive machine learning, where each learning example contains a bag of instances instead of a single feature vector. The term commonly refers to the supervised setting, where ...
  • Revisiting multiple-instance learning via embedded instance selection

    Foulds, James Richard; Frank, Eibe (Springer, 2008)
    Multiple-Instance Learning via Embedded Instance Selection (MILES) is a recently proposed multiple-instance (MI) classification algorithm that applies a single-instance base learner to a propositionalized version of MI ...

James Richard Foulds has 2 co-authors in Research Commons.