@INCOLLECTION{2012:3IPMU,
  author = {Veronica Biazzo and Angelo Gilio and Giuseppe Sanfilippo},
  title = {Coherent Conditional Previsions and Proper Scoring Rules},
  booktitle = {Advances in Computational Intelligence},
  publisher = {Springer},
  year = {2012},
  editor = {Salvatore Greco and Bernadette Bouchon-Meunier and Giulianella Coletti
	and Mario Fedrizzi and Benedetto Matarazzo and Ronald R. Yager},
  volume = {300},
  series = {Communications in Computer and Information Science},
  pages = {146--156},
  note = {ISBN:978-3-642-31723-1},
  abstract = {In this paper we study the relationship between the notion of coherence
	for conditional prevision assessments on a family of finite conditional
	random quantities and the notion of admissibility with respect to
	bounded strictly proper scoring rules. Our work extends recent results
	given by the last two authors of this paper on the equivalence between
	coherence and admissibility for conditional probability assessments.
	In order to prove that admissibility implies coherence a key role
	is played by the notion of Bregman divergence.},
  comment = {<a href="http://www.unipa.it/giuseppe.sanfilippo/pdf/2012/ipmu/IPMU2012_quasiversion.pdf">[A
	version similar to the published paper]</a>},
  doi = {10.1007/978-3-642-31724-8_16},
  isbn = {978-3-642-31723-1},
  issn = {1865-0929},
  location = {Heidelberg},
  scopus = {{2-s2.0-84868266864}},
  url = {http://www.springer.com/computer/ai/book/978-3-642-31723-1}
}

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