Data-Powered Computing
| COMPUTER SCIENCE/DISCRETE MATH I | |
| Topic: | Data-Powered Computing |
| Speaker: | Bernard Chazelle |
| Affiliation: | Princeton University |
| Date: | Monday, April 2 |
| Time/Room: | 11:15am - 12:15pm/S-101 |
Traditional algorithm design is being challenged by the remarkable technological advances in data acquisition of recent years. Today's algorithms must often cope with data that is massive, noisy, uncertain, high-dimensional, nonuniformly priced, streaming, or of low entropy.
As data is fast becoming a major conceptual driver of algorithm design, a new, data-centric approach has been taken, giving rise to sublinear algorithms, low entropy data structures, self-improving algorithms, and online data reconstruction. I will discuss these developments on a few concrete examples.