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Vidya Rajaram

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Publications by Vidya Rajaram (bibliography)

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Stumpf, Simone, Rajaram, Vidya, Li, Lida, Burnett, Margaret, Dietterich, Thomas G., Sullivan, Erin, Drummond, Russell and Herlocker, Jonathan (2007): Toward harnessing user feedback for machine learning. In: Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007. pp. 82-91. Available online

There has been little research into how end users might be able to communicate advice to machine learning systems. If this resource -- the users themselves -- could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved and the users' understanding and trust of the system could improve as well. We conducted a think-aloud study to see how willing users were to provide feedback and to understand what kinds of feedback users could give. Users were shown explanations of machine learning predictions and asked to provide feedback to improve the predictions. We found that users had no difficulty providing generous amounts of feedback. The kinds of feedback ranged from suggestions for reweighting of features to proposals for new features, feature combinations, relational features, and wholesale changes to the learning algorithm. The results show that user feedback has the potential to significantly improve machine learning systems, but that learning algorithms need to be extended in several ways to be able to assimilate this feedback.

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Changes to this page (author)

25 Feb 2010: Enabled abstracts to be shown on Vidya Rajaram's author page.
24 Jul 2007: Author was added to the bibliography

Publication statistics

Publication period:2007-2007
Publication count:1
Number of co-authors:7



Productive colleagues

Vidya Rajaram's 3 most productive colleagues in number of publications:

Margaret Burnett:20
Thomas G. Dietterich:6
Simone Stumpf:5


Collaboration count

Number of publications with 3 favourite co-authors:

Russell Drummond:1
Jonathan Herlocker:1
Erin Sullivan:1

 

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Mar 21

Software design is the act of determining the user's experience with a piece of software. It has nothing to do with how the code works inside, or how big or small the code is. The designer's task is to specify completely and unambiguously the user's whole experience.

-- David Liddle, From Bringing Design to Software, edited by Terry Winograd, 1996

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