16 citations · 34 across the 9 of their papers we have counts for
11 papers
Machine Learning over Static and Dynamic Relational Data
Ahmet Kara, Milos Nikolic, Dan Olteanu +1
This tutorial overviews principles behind recent works on training and maintaining machine learning models over relational data, with an emphasis on the exploitation of the relatio…
F-IVM: Learning over Fast-Evolving Relational Data
Milos Nikolic, Haozhe Zhang, Ahmet Kara +1
F-IVM is a system for real-time analytics such as machine learning applications over training datasets defined by queries over fast-evolving relational databases. We will demonstra…
Maintaining Triangle Queries under Updates
Ahmet Kara, Milos Nikolic, Hung Q. Ngo +2
We consider the problem of incrementally maintaining the triangle queries with arbitrary free variables under single-tuple updates to the input relations. We introduce an approach…
Trade-offs in Static and Dynamic Evaluation of Hierarchical Queries
Ahmet Kara, Milos Nikolic, Dan Olteanu +1
We investigate trade-offs in static and dynamic evaluation of hierarchical queries with arbitrary free variables. In the static setting, the trade-off is between the time to partia…
Incremental Techniques for Large-Scale Dynamic Query Processing
Iman Elghandour, Ahmet Kara, Dan Olteanu +1
Many applications from various disciplines are now required to analyze fast evolving big data in real time. Various approaches for incremental processing of queries have been propo…
Counting Triangles under Updates in Worst-Case Optimal Time
Ahmet Kara, Hung Q. Ngo, Milos Nikolic +2
We consider the problem of incrementally maintaining the triangle count query under single-tuple updates to the input relations. We introduce an approach that exhibits a space-time…