Hope you are all safe and healthy, the next Priberam Machine Learning Seminar
was rescheduled back to its typical time, 13h. We are sorry for any possible inconvenience.
Next Tuesday, June 30th,
Laura Balzano, an associate professor in Electrical Engineering and Computer Science at the University of Michigan will present her work "Preference Modeling with Context-Dependent Salient Features" at
13:00h (zoom link: https://zoom.us/j/89697809357
).
You can register for this event and keep watch on future seminars below:
Food will not be provided but feel free to eat at the same time :) Please note that the seminar is limited to 100 people
and this will work on a 1st come 1st served basis. So please try to be on time if you wish to attend.
Priberam is hiring!
If you are interested in working with us please consult the available positions at priberam.com/careers.
PRIBERAM SEMINARS
-- Zoom
89697809357
__________________________________________________
Priberam Machine Learning Lunch Seminar
Speaker:
Laura Balzano (U. Michigan)
Venue:
https://zoom.us/j/89697809357
Date: Tuesday,
June 30th, 2020
Time: 13:00
Title:
Preference
Modeling with Context-Dependent Salient Features
Abstract:
Laura
Balzano is an associate professor in Electrical Engineering and Computer Science at the University of Michigan, and a member of the Institute for Advanced Study for the special year on Optimization, Statistics, and Theoretical Machine Learning. She is a recipient
of the NSF Career Award, a Fulbright fellowship, ARO Young Investigator Award, AFOSR Young Investigator Award, and faculty fellowships from Intel and 3M. Laura received a BS from Rice University, MS from UCLA, and PhD from the University of Wisconsin, all
in Electrical and Computer Engineering. Her main research focus is on modeling with big, messy data — highly incomplete or corrupted data, uncalibrated data, and heterogeneous data — and its applications in machine learning, environmental monitoring, and computer
vision. Her expertise is in statistical signal processing, matrix factorization, and optimization.