From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events

Giuseppe Sanfilippo
Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence, PMLR R10:735-744, 2012.

Abstract

In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) intervalvalued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of conditioning events which are consistent with the given initial assessment. Quasi additivity assures coherence for the obtained conditional probabilities. In order to reach our goal we define a finite sequence of conditional probabilities by exploiting some theoretical results on g-coherence. In particular, we use solutions of a finite sequence of linear systems.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR10-sanfilippo12a, title = {From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events}, author = {Sanfilippo, Giuseppe}, booktitle = {Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence}, pages = {735--744}, year = {2012}, editor = {de Freitas, Nando and Murphy, Kevin}, volume = {R10}, series = {Proceedings of Machine Learning Research}, month = {14--18 Aug}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/r10/main/assets/sanfilippo12a/sanfilippo12a.pdf}, url = {https://proceedings.mlr.press/r10/sanfilippo12a.html}, abstract = {In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) intervalvalued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of conditioning events which are consistent with the given initial assessment. Quasi additivity assures coherence for the obtained conditional probabilities. In order to reach our goal we define a finite sequence of conditional probabilities by exploiting some theoretical results on g-coherence. In particular, we use solutions of a finite sequence of linear systems.}, note = {Reissued by PMLR on 04 October 2026.} }
Endnote
%0 Conference Paper %T From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events %A Giuseppe Sanfilippo %B Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence %C Proceedings of Machine Learning Research %D 2012 %E Nando de Freitas %E Kevin Murphy %F pmlr-vR10-sanfilippo12a %I PMLR %P 735--744 %U https://proceedings.mlr.press/r10/sanfilippo12a.html %V R10 %X In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) intervalvalued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of conditioning events which are consistent with the given initial assessment. Quasi additivity assures coherence for the obtained conditional probabilities. In order to reach our goal we define a finite sequence of conditional probabilities by exploiting some theoretical results on g-coherence. In particular, we use solutions of a finite sequence of linear systems. %Z Reissued by PMLR on 04 October 2026.
APA
Sanfilippo, G.. (2012). From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events. Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R10:735-744 Available from https://proceedings.mlr.press/r10/sanfilippo12a.html. Reissued by PMLR on 04 October 2026.

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