Data-driven Discovery of Models (D3M)
Final Program
This workshop is about data-driven approaches to model discovery. These approaches aim at developing systems that enable users with subject matter expertise but no data science background to create empirical models of real, complex processes. As a result, 1) subject matter experts are empowered to create empirical models without the need for data scientists, and 2) expert data scientists experience increased productivity through automation.
Workshop Program
8:30 Welcome
8:35 Paper Session
- Jialin Dong, Kai Yang, and Yuanming Shi
- Keith Levin, Avanti Athreya, Minh Tang, Vince Lyzinski, and Carey Priebe
10:05 Break
10:20 Paper Session
- Dataset Selection for Controlling Swarms by Visual Demonstration (25 min)
- Karan Budhraja and Tim Oates
11:00 Invited Contribution
- Horst Samulowitz, IBM TJ Watson
11:45 Wrap-up
11:50 Lunch
Organization
Co-chairs
- Ishanu Chattopadhyay, University of Chicago
- Christophe Giraud-Carrier, Brigham Young University
- Madeleine Udell, Cornell University
Please direct questions to Christophe Giraud-Carrier
Program Committee
- Rauf Izmailov, Vencore Labs
- Avi Pfeffer, Charles River Analytics Inc.
- Carey Priebe, Johns Hopkins University
- Juliana Freire, New York University
- Michael Mahoney, University of California Berkeley
- Stephen Bach, Stanford University
- Scott Langevin, Unchartered Software
- Mukesh Dalal, Charles River Analytics
- Hod Lipson, Columbia University
- Artur Dubrawski, Carnegie Mellon University
- Eric Nyberg, Carnegie Mellon University
- Kyle Miller, Carnegie Mellon University
- Barnabas Poczos, Carnegie Mellon University
- William Cleveland, Purdue University
- Mayank Kejriwal, University of Southern California, ISI