- Series
- ACO Student Seminar
- Time
- Friday, October 19, 2018 - 1:05pm for 1 hour (actually 50 minutes)
- Location
- Skiles 005
- Speaker
- Samira Samadi – CS, Georgia Tech – ssamadi6@gatech.edu – https://sites.google.com/site/ssamadi/
- Organizer
- He Guo
We investigate whether the standard dimensionality reduction techniques
inadvertently produce data representations with different fidelity for
two different populations. We show on several real-world datasets, PCA
has higher reconstruction error on population
A than B (for example, women versus men or lower versus higher-educated
individuals). This can happen even when the dataset has similar number
of samples from A and B . This motivates our study of dimensionality
reduction techniques which maintain similar fidelity
for A as B . We give an efficient algorithm for finding a projection
which is nearly-optimal with respect to this measure, and evaluate it on
several datasets. This is a joint work with Uthaipon
Tantipongpipat, Jamie Morgenstern, Mohit Singh, and Santosh Vempala.