Graduate Seminar: Peter Lindner: The Theory of Infinite Probabilistic Databases

Tuesday, August 24, 2021, 10:00am

Location: Online Session
Meeting ID: 976 2124 1861
Passcode: 592961

Speaker: Peter Lindner


The Theory of Infinite Probabilistic Databases​

Probabilistic (relational) databases extend the conventional relational database model by probability distributions over database instances.
Such models are desirable for, and applicable to, a wide range of scenarios where data is subject to uncertainty. For a long time, the theoretical state of the art was to view a probabilistic database as a discrete probability space with only finitely many possible outcome instances.

In this talk, we give an overview over our contributions regarding the extension of this model, along with various key concepts, to infinite probability spaces. This is required to support basic probabilistic methods, like continuous noise models and tackles default shortcomings of the restriction to discrete spaces. To this end, we present and explore a suitable unifying framework for infinite probabilistic databases that is based on point processes. This covers all applications of interest, and complies with the desired requirements for such a framework. It's inherent abstractness allows us to discuss central notions from the theory of probabilistic databases like query semantics and independence assumptions from a plain probability theoretic point of view.