The Goals of this workshop are to examine some recent research on
Machine Learning in Design, and also to develop a Taxonomy for Machine
Learning in Design. Participants should come prepared to
describe the position of their work on the proposed Taxonomy
(see http://cs.wpi.edu/~dcb/AID/taxonomy.html ),
and suggest extensions to it if your work doesnt fit into the proposed
scheme.
Each speaker will get 15 minutes to speak, and 3 mins for questions.
We will be very strict with the timekeeping!
8:45 Opening Comments, Introductions {Brown & Goel}
Part 1
9:00 Brandish, Hague & Taleb-Bendiab + Discussion/Questions
9:18 Branki, Bridges & Wallis + Discussion/Questions
9:36 Prabhakar & Basu + Discussion/Questions
9:54 Schwabacher, Ellman & Hirsch + Discussion/Questions
10:12 Tang + Discussion/Questions
Note: The paper by Manfaat, Duffy & Lee will not be presented.
10:30-11:00 Coffee Break
Part 2
11:00 Grecu & Brown
11:15 Discussion/Questions (about Taxonomy for ML in D).
11:30 Workshop Discussion 1: Learning in Design systems {Goel}
What kinds of learning in design have been tried?
Do they fit in the Taxonomy?
How can the Taxonomy be extended?
12:00 Workshop Discussion 2: Distributed Learning {Brown}
Repetition of above, for distributed design systems.
12:35 Review, Summary & Conclusions {All}
What spaces in the Taxonomy need to be researched next?
12:45 End of Workshop