Consistency in a model for distributed learning with specialists

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

Motivated by sensor networks and traditional methods of statistical pattern recognition, a model for distributed learning is formulated. The model is in line with learning models considered in the context of Stone-type classifiers, but differs in the dependency structure of the sampling process; questions of universal consistency are addressed.

Original languageEnglish (US)
Number of pages1
JournalIEEE International Symposium on Information Theory - Proceedings
StatePublished - Oct 20 2004
EventProceedings - 2004 IEEE International Symposium on Information Theory - Chicago, IL, United States
Duration: Jun 27 2004Jul 2 2004

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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