Portrait on green background, header for New England Machine Learning Day event page
May 12, 2017

New England Machine Learning Day 2017

Location: Cambridge, MA, USA

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
Intelligent robots redux

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

Steering committee

  • Ryan Adams, Harvard University
  • Adam Tauman Kalai, Microsoft Research
  • Joshua Tenenbaum, Massachusetts Institute of Technology

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