The duality diagram in data analysis: Examples of modern applications
Omar De la Cruz, Susan Holmes

TL;DR
The paper revisits the duality diagram approach, illustrating its modern applications in data integration and showing its relevance as a precursor to kernel methods in complex data analysis.
Contribution
It introduces the duality diagram technique, demonstrating its new uses with various metrics and combinations, and connects it to modern kernel-based approaches.
Findings
Provides contemporary examples of duality diagrams in data integration
Shows the technique's versatility with different metrics and diagram combinations
Highlights the duality diagram as a precursor to kernel methods
Abstract
Today's data-heavy research environment requires the integration of different sources of information into structured data sets that can not be analyzed as simple matrices. We introduce an old technique, known in the European data analyses circles as the Duality Diagram Approach, put to new uses through the use of a variety of metrics and ways of combining different diagrams together. This issue of the Annals of Applied Statistics contains contemporary examples of how this approach provides solutions to hard problems in data integration. We present here the genesis of the technique and how it can be seen as a precursor of the modern kernel based approaches.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
