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Using the Theory of Regular Functions to Formally Prove the ε-Optimality of Discretized Pursuit Learning Algorithms.

Xuan ZhangB. John OommenOle-Christoffer GranmoLei Jiao
Published in: IEA/AIE (1) (2014)
Keyphrases
  • learning algorithm
  • active learning
  • decision trees
  • training data
  • machine learning algorithms
  • theoretical framework
  • data sets
  • reinforcement learning
  • learning process
  • labeled data
  • general theory
  • pareto optimality