Fellow Prof Dan Olteanu's Project Receives $100,000 Research Gift
St Cross Fellow Professor Dan Olteanu is the leader of the FDB (Factorised Database) Project, which has just been awarded an unrestricted research gift of 100,000 USD from Infor Corp (USA) to support on-going work on in-database machine learning.
Of the project, Dan said:
Our goal is to build a scalable system for training machine learning models over relational databases. We recently showed that popular machine learning models, including decision trees, factorization machines, and support vector machines can be trained directly inside a database engine by reformulating the training task as the problem of evaluating batches of relational queries over the input database. Our approach comes with both theoretical and practical benefits. It enjoys lower computational complexity than the existing approaches, which means in practice training over larger datasets and orders-of-magnitude faster than state-of-the-art analytics systems.
Dr Kurt Stirewalt, Vice President of Software Development, Infor says:
Infor is pleased to support the work of Professor Dan Olteanu on the FDB project, which addresses a fundamental obstacle to scaling machine learning to large data sets such as we encounter when forecasting demand in retail contexts.
18 December 2018