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Found 8 papers, 2 papers with code
CHORUS: Foundation Models for Unified Data Discovery and Exploration
On all three tasks, we show that a foundation-model-based approach outperforms the task-specific models and so the state of the art.
Functional Collection Programming with Semi-Ring Dictionaries
We developed SDQL, a statically typed language that can express relational algebra with aggregations, linear algebra, and functional collections over data such as relations and matrices using semi-ring dictionaries.
The Relational Data Borg is Learning
This work is the outcome of extensive collaboration of the author with colleagues from RelationalAI, in particular Mahmoud Abo Khamis, Molham Aref, Hung Ngo, and XuanLong Nguyen, and from the FDB research project, in particular Ahmet Kara, Milos Nikolic, Maximilian Schleich, Amir Shaikhha, Jakub Zavodny, and Haozhe Zhang.
Multi-layer Optimizations for End-to-End Data Analytics
We consider the problem of training machine learning models over multi-relational data.
Rk-means: Fast Clustering for Relational Data
When the data matrix needs to be obtained from a relational database via a feature extraction query, the computation cost can be prohibitive, as the data matrix may be (much) larger than the total input relation size.
Functional Aggregate Queries with Additive Inequalities
This new width is sandwiched between the submodular and the fractional hypertree widths.
Declarative Statistical Modeling with Datalog
By virtue of extending Datalog, our framework offers a natural integration with the database, and has a robust declarative semantics.
10^(10^6) Worlds and Beyond: Efficient Representation and Processing of Incomplete Information
Current systems and formalisms for representing incomplete information generally suffer from at least one of two weaknesses.
Databases H.2.1; H.2.4
