Venue:
Microsoft Research New England
Horace Mann Conference Room
One Memorial Drive
Cambridge, MA 02142
Registration: Registration is now closed. Thank you for your interest in this year’s Machine Learning and we hope to see you next year!
The sixth annual New England Machine Learning Day will be Friday, May 12, 2017, at Microsoft Research New England, One Memorial Drive, Cambridge, MA 02142. The event will bring together local academics and researchers in Machine Learning, Artificial Intelligence, and their applications. There will be a lively poster session during lunch.
Interested in helping improve fairness and reduce bias/discrimination in ML? Attend New England Machine Learning Hackathon: Hacking Bias in ML, the day before, Thursday May 11, at the same location.
For talk abstracts, see the Agenda tab above.
Schedule
Time | Session |
---|---|
9:55–10:00
|
Opening remarks
|
10:00–10:30
|
Leslie Pack Kaelbling, Massachusetts Institute of Technology |
10:35–11:05 | Alexander Rush, Harvard University Structured attention networks |
11:10–11:40 | Lester Mackey, Microsoft Research Measuring sample quality with Stein’s method |
11:40–1:45 | Lunch and posters |
1:45–2:15 | Thomas Serre, Brown University What are the visual features underlying human versus machine vision? |
2:20–2:50 | David Sontag, Massachusetts Institute of Technology Causal inference via deep learning |
2:50–3:20 | Coffee break |
3:20–3:50 | Roni Khardon, Tufts University Effective variational inference in non-conjugate 2-level latent variable models |
3:55–4:25 | Tina Eliassi-Rad, Northeastern University Learning, mining and graphs |
4:30–5:00 | Erik Learned-Miller, University of Massachusetts Amherst Bootstrapping intelligence with motion estimation |
Organizers
- David Cox, Harvard University
- Adam Tauman Kalai, Microsoft Research (chair)
- Ankur Moitra, Massachusetts Institute of Technology
- Kate Saenko, Boston University
Poster chairs
- Mike Hughes, Harvard University
- Genevieve Patterson, Microsoft Research
Steering committee
- Ryan Adams, Harvard University
- Adam Tauman Kalai, Microsoft Research
- Joshua Tenenbaum, Massachusetts Institute of Technology