Browsing by Subject "Expected utility"

Now showing 1 - 3 of 3

Open Access
Another characterization of expected Scott-Suppes Utility Representation
(2021-01) Yıldız, Furkan
This thesis provides a new characterization of Expected Scott-Suppes Utility Representation (ESSUR). ESSUR combines the Expected Utility Repre-sentation with the Scott-Suppes Utility Representation. The latter represents semiorders that formalize preferences with intransitive indi˙erences. Dalkıran, Dokumacı, and Kara (2018) were the first to provide an axiomatic character-ization of ESSUR. In this study, we provide another characterization start-ing with the axioms of Candeal and Indurain (2010). Candeal and Indurain (2010) provide an axiomatic characterization of Scott-Suppes representations for semiorders on uncountably infinite sets. Therefore, we identify the axioms required on top of those of Candeal and Indurain (2010) so that we obtain a linear Scott-Suppes representation, i.e., another characterization of ESSUR.
Open Access
Differential privacy with bounded priors: Reconciling utility and privacy in genome-wide association studies
(ACM, 2015-10) Tramèr, F.; Huang, Z.; Hubaux J.-P.; Ayday, Erman
Differential privacy (DP) has become widely accepted as a rigorous definition of data privacy, with stronger privacy guarantees than traditional statistical methods. However, recent studies have shown that for reasonable privacy budgets, differential privacy significantly affects the expected utility. Many alternative privacy notions which aim at relaxing DP have since been proposed, with the hope of providing a better tradeoff between privacy and utility. At CCS'13, Li et al. introduced the membership privacy framework, wherein they aim at protecting against set membership disclosure by adversaries whose prior knowledge is captured by a family of probability distributions. In the context of this framework, we investigate a relaxation of DP, by considering prior distributions that capture more reasonable amounts of background knowledge. We show that for different privacy budgets, DP can be used to achieve membership privacy for various adversarial settings, thus leading to an interesting tradeoff between privacy guarantees and utility. We re-evaluate methods for releasing differentially private χ2-statistics in genome-wide association studies and show that we can achieve a higher utility than in previous works, while still guaranteeing membership privacy in a relevant adversarial setting. © 2015 ACM.
Open Access
Expected Scott-Suppes utility representation
(Academic Press, 2018) Dalkıran, Nuh Aygün; Dokumacı, O. E.; Kara, Tarık
We provide an axiomatic characterization for an expected Scott-Suppes utility representation. Such a characterization is the natural analog of the von Neumann-Morgenstern expected utility theorem for semiorders and it is noted as an open problem by Fishburn (1968). Expected Scott-Suppes utility representation is analytically tractable and can be used in applications that study preferences with intransitive indifference under uncertainty. Our representation offers a decision-theoretical interpretation for epsilon equilibrium as well.