The first workshop on ‘Machine Learning for Creativity’ is held along with SIGKDD-2017 to address one of the elusive goals of artificial intelligence - “Can Machines become creative like humans?”. The goal of this workshop is to generate interest among the machine learning and data science community in this upcoming field by concentrating on applications of machine learning in creative domains
- Paper submission date: May 26, 2017
- Acceptance notification date: June 16, 2017
- Workshop date: August 14, 2017
- Flavio du Pin Calmon, Harvard University
- Mark Riedl, Georgia Institute of Technology
- Nick Montfort, Massachusetts Institute of Technology
Suggested topics include, but not restricted to,
- Formulations/ perspectives about creativity.
- Evaluation metrics for creativity.
- Multi-modal systems for creativity.
- Large-scale analytics with creativity understanding.
- Case-studies of creative generation process.
- Collaborative interfaces for creative human-computer interaction.
- Survey reports or benchmark dataset
We solicit submission of papers of 4 to 10 pages representing reports of original research, preliminary research results, survey and dataset papers, case studies, proposals for new work, and position papers. We also seek poster submissions based on recently published work (please indicate the conference published).
Following KDD conference tradition, reviews are single-blind, and author names and affiliations should be listed. If accepted, at least one of the authors must attend the workshop to present the work. The submitted papers must be written in English and formatted in the double column standard according to the ACM Proceedings Template, Tighter Alternate style (http://www.acm.org/publications/proceedings-template). The papers should be in PDF format and submitted via the EasyChair submission site (https://easychair.org/conferences/?conf=creativeai17). The workshop website will archive the published papers.
Looking forward to see you at KDD 2017!
Anush Sankaran (IBM Research)
Karthik Sankaranarayanan (IBM Research)
Lav R. Varshney (UIUC)
Douglas Eck (Google Brain)
Kush R. Varshney (IBM Research)
Francois Pachet (Sony CSL)
Priyanka Agrawal (IBM Research)
Disha Shrivastava (IBM Research)