We study two succinct representation systems for relational data based on relational algebra
expressions with unions, Cartesian products, and singleton relations: f-representations …

Incomplete data accompanies our life processes and covers almost all fields of scientific
studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how …

This paper overviews factorized databases and their application to machine learning. The
key observation underlying this work is that state-of-the-art relational query processing …

We study here fundamental issues involved in top-k query evaluation in probabilistic
databases. We consider simple probabilistic databases in which probabilities are associated …

A common approach to data analysis involves understanding and manipulating succinct
representations of data. In earlier work, we put forward a succinct representation system for …

A paramount challenge in probabilistic databases is the scalable computation of
confidences of tuples in query results. This paper introduces an efficient secondary-storage …

We introduce F-IVM, a unified incremental view maintenance (IVM) approach for a variety of
tasks, including gradient computation for learning linear regression models over joins, matrix …

Factorised databases are relational databases that use compact factorised representations
at the physical layer to reduce data redundancy and boost query performance. This paper …

This paper introduces a deterministic approximation algorithm with error guarantees for
computing the probability of propositional formulas over discrete random variables. The …

We introduce a representation system for relational data based on algebraic factorisation
using distributivity of product over union and commutativity of product and union. We give …