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AAAI
2008

Exposing Parameters of a Trained Dynamic Model for Interactive Music Creation

14 years 13 days ago
Exposing Parameters of a Trained Dynamic Model for Interactive Music Creation
As machine learning (ML) systems emerge in end-user applications, learning algorithms and classifiers will need to be robust to an increasingly unpredictable operating environment. In many cases, the parameters governing a learning system cannot be optimized for every user scenario, nor can users typically manipulate parameters defined in the space and terminology of ML. Conventional approaches to user-oriented ML systems have typically hidden this complexity from users by automating parameter adjustment. We propose a new paradigm, in which model and algorithm parameters are exposed directly to end-users with intuitive labels, suitable for applications where parameters cannot be automatically optimized or where there is additional motivation
Dan Morris, Ian Simon, Sumit Basu
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where AAAI
Authors Dan Morris, Ian Simon, Sumit Basu
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