November 17, 2015
4:00PM - 5:00PM
Dreese Lab 264
Add to Calendar
2015-11-17 17:00:00
2015-11-17 18:00:00
Topology, Geometry & Data Seminar - Jose Perea
Title: Projective coordinates for the analysis of dataSpeaker: Jose Perea (MSU)Abstract: Why do we use topology to analyze data? Is it because it sounds good? maybe... or is it because we have readily computable invariants? perhaps... but in the end, it is because we hope the invariants we compute can ultimately shed light on the data itself. I will show in this talk how one can use persistent (co)homology, the Brown representability theorem, and other tools, to produce maps from data to the appropriate real and complex projective spaces. I will give examples of how these projective coordinates provide useful representations for certain data sets.Seminar URL: http://www.tgda.osu.edu/tgda-seminar.html
Dreese Lab 264
OSU ASC Drupal 8
ascwebservices@osu.edu
America/New_York
public
Date Range
Add to Calendar
2015-11-17 16:00:00
2015-11-17 17:00:00
Topology, Geometry & Data Seminar - Jose Perea
Title: Projective coordinates for the analysis of dataSpeaker: Jose Perea (MSU)Abstract: Why do we use topology to analyze data? Is it because it sounds good? maybe... or is it because we have readily computable invariants? perhaps... but in the end, it is because we hope the invariants we compute can ultimately shed light on the data itself. I will show in this talk how one can use persistent (co)homology, the Brown representability theorem, and other tools, to produce maps from data to the appropriate real and complex projective spaces. I will give examples of how these projective coordinates provide useful representations for certain data sets.Seminar URL: http://www.tgda.osu.edu/tgda-seminar.html
Dreese Lab 264
Department of Mathematics
math@osu.edu
America/New_York
public
Title: Projective coordinates for the analysis of data
Speaker: Jose Perea (MSU)
Abstract: Why do we use topology to analyze data? Is it because it sounds good? maybe... or is it because we have readily computable invariants? perhaps... but in the end, it is because we hope the invariants we compute can ultimately shed light on the data itself. I will show in this talk how one can use persistent (co)homology, the Brown representability theorem, and other tools, to produce maps from data to the appropriate real and complex projective spaces. I will give examples of how these projective coordinates provide useful representations for certain data sets.
Seminar URL: http://www.tgda.osu.edu/tgda-seminar.html
