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