A Note on Parameter Tuning for On-Line Shifting Algorithms
2003
Technical Report
ei
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.
Author(s): | Bousquet, O. |
Year: | 2003 |
Day: | 0 |
Department(s): | Empirische Inferenz |
Bibtex Type: | Technical Report (techreport) |
Institution: | Max Planck Institute for Biological Cybernetics, Tübingen, Germany |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
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BibTex @techreport{2294, title = {A Note on Parameter Tuning for On-Line Shifting Algorithms}, author = {Bousquet, O.}, organization = {Max-Planck-Gesellschaft}, institution = {Max Planck Institute for Biological Cybernetics, T{\"u}bingen, Germany}, school = {Biologische Kybernetik}, year = {2003}, doi = {} } |