A Note on Parameter Tuning for On-Line Shifting Algorithms

Bousquet, O

Item

ITEM ACTIONSEXPORT

Add to Basket

Please note that a newer version of this item is available:
https://pure.mpg.de/pubman/item/item_1792630_2

DetailsSummary

Released

Report

A Note on Parameter Tuning for On-Line Shifting Algorithms

MPS-Authors

/persons/resource/persons83824

Bousquet, O
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Bousquet, O.(2003). A Note on Parameter Tuning for On-Line Shifting Algorithms.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-DDF2-F

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.