@techreport{2294,
  title = {A Note on Parameter Tuning for On-Line Shifting Algorithms},
  abstract = {In this short note, building on ideas of M. Herbster [2] we propose a method for automatically tuning the
  parameter of the FIXED-SHARE algorithm proposed by Herbster and
  Warmuth [3] in the context of on-line learning with
  shifting experts. We show that this can be done with a memory
  requirement of $O(nT)$ and that the additional loss incurred by
  the tuning is the same as the loss incurred for estimating the
  parameter of a Bernoulli random variable.},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics, T{\"u}bingen, Germany},
  school = {Biologische Kybernetik},
  year = {2003},
  slug = {2294},
  author = {Bousquet, O.}
}