- Series
- ACO Distinguished Lecture
- Time
- Tuesday, November 1, 2011 - 4:30pm for 1 hour (actually 50 minutes)
- Location
- Klaus 1116
- Speaker
- Ravi Kannan – Microsoft Research India
- Organizer
- Robin Thomas
Please Note: There will be a reception in the Atrium of the Klaus building at 4PM.
Modeling data as high-dimensional (feature) vectors is a staple in Computer
Science, its use in ranking web pages reminding us again of its effectiveness.
Algorithms from Linear Algebra (LA) provide a crucial toolkit. But, for modern
problems with massive data, these algorithms may take too long. Random
sampling to reduce the size suggests itself. I will give a from-first-principles
description of the LA connection, then discuss sampling techniques developed
over the last decade for vectors, matrices and graphs. Besides saving time,
sampling leads to sparsification and compression of data.
Speaker's bio