Seminar Details
2020-02-25 (14:00) : Binarizing Johnson-Lindenstrauss transforms
At Euler building (room A.002)
Organized by Mathematical Engineering
Speaker :
Stollenwerk, Alexander
Abstract :
In many problems from data science, the encountered data is massive and encoded by high-dimensional vectors. For applications it is therefore appealing to first reduce its dimensionality before performing computations. If enough geometric information between data vectors is preserved, then the problem can be solved approximately using the embedded data. In this talk, we will focus on the problem of encoding a set of high-dimensional vectors into a small number of bits, while approximately preserving their pairwise Euclidean distances. By binarizing fast Johnson-Lindenstrauss transforms, we will see that this can be achieved efficiently, even for infinite data sets of low-complexity. The talk is based on joint work with Sjoerd Dirksen.