A space-bounded learning algorithm for axis-parallel rectangles

  • Foued Ameur
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 904)


We consider the on-line learnability from equivalence queries only of axis-parallel rectangles over the discrete grid {1,..., n} d (BOX n d ). Further we impose the restriction of “k-space-bounded learning”, i.e. the information the learner can store about the history of the learning protocol is restricted to the previous hypothesis and at most k of the examples seen. Our result improves the best known algorithm about learning BOX n d due to Chen and Maass [9]. Their algorithm has learning complexity O(d2 log n) requires space Θ(d2logn) and time Ω(log(d2log n)) for each learning step. We present an on-line learning algorithm for BOX n d with the same learning complexity, time complexity O(d3log n) which is 2d-space-bounded.


Learning Algorithm Target Concept Learning Complexity Membership Query Equivalence Query 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Foued Ameur
    • 1
  1. 1.Heinz Nixdorf Institute and Dept. of Mathematics & Computer ScienceUniversity of PaderbornPaderbornGermany

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