Browsing by Author "Kulesza, Todd"

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End-user debugging of machine-learned programs : toward principles for baring the logic

Kulesza, Todd; Stumpf, Simone; Riche, Yann; Burnett, Margaret; Wong, Weng-Keen; Oberst, Ian; Moor, Travis; McIntosh, Kevin; Bice, Forrest (2009?)

Many applications include machine learning algorithms intended to learn “programs” (rules of behavior) from an end user’s actions. When these learned programs are wrong, their users receive little explanation as to why, ...
End-user feature engineering in the presence of class imbalance

Oberst, Ian; Moore, Travis; Wong, Weng-Keen; Kulesza, Todd; Stumpf, Simone; Riche, Yann; Burnett, Margaret (2009-11-02)

Intelligent user interfaces, such as recommender systems and email classifiers, use machine learning algorithms to customize their behavior to the preferences of an end user. Although these learning systems are somewhat ...
Toward end-user debugging of machine-learned programs

Kulesza, Todd (2009-12-02)

The results of a machine learning from user behavior can be thought of as a program, and like all programs, it may need to be debugged. Providing ways for the user to debug it matters because without the ability to fix e ...

Now showing items 1-3 of 3

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