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IDA Machine Learning Seminars - Spring 2019

Wednesday, February 27, 3.15 pm, 2019

Reliable Semi-Supervised Learning when Labels are Missing at Random
Dave Zachariah
, Department of Information Technology, Division of Systems and Control, Uppsala University
Abstract: Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data. Unlabeled data is, however, not guaranteed to improve classification performance and has in fact been reported to impair the performance in certain cases. In this talk we discuss some fundamental limitations to semi-supervised learning and restrictive assumptions which result in unreliable classifiers. We also propose a learning approach that relaxes such assumptions and is capable of providing classifiers that reliably quantify the label uncertainty.
Location: Ada Lovelace (Visionen)
Organizer: Fredrik Lindsten

Wednesday, March 27, 3.15 pm, 2019

Henrik Boström
, Dept of Software and Computer Systems, KTH Royal Institute of Technology
Abstract: TBA
Location: TBA
Organizer: Oleg Sysoev

Wednesday, April 24, 3.15 pm, 2019


Abstract: TBA
Location: TBA
Organizer: TBA

Wednesday, May 15, 3.15 pm, 2019 (Note the date)

Florian T. Pokorny
, Robotics, Perception and Learning Lab, KTH Royal Institute of Technology.
Abstract: TBA
Location: TBA
Organizer: Mattias Villani

Future Seminars

Fall 2019   |   Spring 2020

Past Seminars

Fall 2018   |   Spring 2018   |   Fall 2017   |   Spring 2017   |   Fall 2016   |   Spring 2016  |   Fall 2015  
Spring 2015   |   Fall 2014

The seminars are typically held every fourth Wednesday at 15.15-16.15 in Ada Lovelace (Visionen).
For further information, or if you want to be notified about the seminars by e-mail, please contact Mattias Villani.

Page responsible: Mattias Villani
Last updated: 2019-02-21