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What and Who
Title:Machine Teaching
Speaker:Adish Singla
coming from:Max Planck Institute for Software Systems
Speakers Bio:
Event Type:Joint Lecture Series
Visibility:D1, D2, D3, INET, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Wednesday, 6 February 2019
Duration:60 Minutes
Building:E1 5
Much of the research in machine learning has focused on designing algorithms for discovering knowledge from data and learning a target model. What if there is a ``teacher" who knows the target already, and wants to steer the ``learner" towards this target as quickly as possible?  For instance, in an educational setting, the teacher (e.g., a tutoring system) has an educational goal that she wants to communicate to a student via a set of demonstrations and lessons; in adversarial attacks known as training-set poisoning, the teacher (e.g., a hacking algorithm) manipulates the behavior of a machine learning system by maliciously modifying the training data. This lecture will provide an overview of machine teaching and cover the following three aspects: (i) how machine teaching differs from machine learning, (ii) highlight the problem space of machine teaching across different dimensions, and (iii) discuss our recent work on developing teaching algorithms for human learners.
Name(s):Jennifer Müller
EMail:--email address not disclosed on the web
Video Broadcast
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Tags, Category, Keywords and additional notes
Attachments, File(s):
Jennifer Müller/MPI-INF, 09/05/2018 01:14 PM
Last modified:
Uwe Brahm/MPII/DE, 02/06/2019 07:01 AM
  • Jennifer Müller, 01/10/2019 08:41 AM
  • Annika Meiser, 12/04/2018 10:22 AM
  • Uwe Brahm, 09/12/2018 05:55 PM
  • Jennifer Müller, 09/05/2018 01:14 PM -- Created document.