Seminar
Parent Program: | |
---|---|
Location: | MSRI: Simons Auditorium |
Joint work with Rayan Saab and Tina Woolf
Binary, or one-bit, representations of dataarise naturally in many applications, and are appealing in both hardware implementations and algorithm design. In this talk, we provide a brief background to sparsity and 1-bit measurements, and then present new results on the problem of data classification from binary data that proposes a framework with low computation and resource costs. We illustrate the utility of the proposed approach through stylized and realistic numerical experiments, provide a theoretical analysis for a simple case, and discuss future directions.
No Notes/Supplements Uploaded
No Video Files Uploaded