Scalable algorithms for aggregating disparate forecasts of probability

J. B. Predd, S. R. Kulkarni, H. V. Poor, D. N. Osherson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, computational aspects of the panel aggregation problem are addressed. Motivated primarily by applications of risk assessment, an algorithm is developed for fusing large corpora of internally incoherent probability assessments. The algorithm is characterized by a provable performance guarantee, and is demonstrated to be orders of magnitude faster than existing tools when tested on several real-world data-sets. In addition, unexpected connections between research in risk assessment and wireless sensor networks are exposed, as several key ideas are illustrated to be useful in both fields.

Original languageEnglish (US)
Title of host publication2006 9th International Conference on Information Fusion, FUSION
DOIs
StatePublished - Dec 1 2006
Event2006 9th International Conference on Information Fusion, FUSION - Florence, Italy
Duration: Jul 10 2006Jul 13 2006

Publication series

Name2006 9th International Conference on Information Fusion, FUSION

Other

Other2006 9th International Conference on Information Fusion, FUSION
CountryItaly
CityFlorence
Period7/10/067/13/06

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems

Keywords

  • Aggregation
  • Forecasting
  • Fusion
  • Risk assessment
  • Sensor networks

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