July 13-14, 2021
Foundations of Data Science Institute (FODSI)
In recent years there has been increasing interest in using machine learning to improve the performance of classical algorithms in computer science, by fine-tuning their behavior to adapt to the properties of the input distribution. This “data-driven” or “learning-based” approach to algorithm design has the potential to significantly improve the efficiency of some of the most widely used algorithms. For example, it has been used to design better data structures, online algorithms, streaming and sketching algorithms, market mechanisms and algorithms for combinatorial optimization, similarity search and inverse problems. This virtual workshop will feature talks from experts at the forefront of this exciting area.