Following the Perturbed Leader for online structured learning

Alon Cohen, Tamir Hazan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We investigate a new Follow the Perturbed Leader (FTPL) algorithm for online structured prediction problems. We show a regret bound which is comparable to the state of the art of FTPL algorithms and is comparable with the best possible regret in some cases. To better understand FTPL algorithms for online structured learning, we present a lower bound on the regret for a large and natural class of FTPL algorithms that use logconcave perturbations. We complete our investigation with an online shortest path experiment and empirically show that our algorithm is both statistically and computationally efficient.

Original languageEnglish
Title of host publication32nd International Conference on Machine Learning, ICML 2015
EditorsDavid Blei, Francis Bach
Pages1034-1042
Number of pages9
ISBN (Electronic)9781510810587
StatePublished - 2015
Externally publishedYes
Event32nd International Conference on Machine Learning, ICML 2015 - Lile, France
Duration: 6 Jul 201511 Jul 2015

Publication series

Name32nd International Conference on Machine Learning, ICML 2015
Volume2

Conference

Conference32nd International Conference on Machine Learning, ICML 2015
Country/TerritoryFrance
CityLile
Period6/07/1511/07/15

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Science Applications

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