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September 2017

Beyond Big Data

September 7 @ 4:00 pm - 5:00 pm
MIT Building 34, Room 401B, The Grier Room (34-401B)
50 Vassar Street, Cambridge, MA 02139 United States
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Speaker: Matthew Salganik (Princeton University) The digital age has transformed the ways that researchers are able to study social behavior. These new opportunities mean that the future of social research will involve combining approaches from social scientists and data scientists, a hybrid that is often called computational social science. After providing some perspective on this growing field, the talk will focus on the Fragile Families Challenge, a scientific mass collaboration involving hundreds of social scientists and data scientists working together…

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New Provable Techniques for Learning and Inference in Probabilistic Graphical Models

September 8 @ 11:00 am - 12:00 pm
MIT Building E18, Room 304, The Ford Building (E18-304)
50 Ames Street, Cambridge, MA 02139 United States
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Speaker: Andrej Risteski (Princeton University) A common theme in machine learning is succinct modeling of distributions over large domains. Probabilistic graphical models are one of the most expressive frameworks for doing this. The two major tasks involving graphical models are learning and inference. Learning is the task of calculating the “best fit” model parameters from raw data, while inference is the task of answering probabilistic queries for a model with known parameters (e.g. what is the marginal distribution of a…

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Fast and Slow Learning from Reviews

September 12 @ 4:30 pm - 5:30 pm
MIT Building 32, Room 141, The Stata Center (32-141)
32 Vassar Street, Cambridge, MA 02139 United States
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Speaker: Daron Acemoglu (MIT) Many online platforms present summaries of reviews by previous users. Even though such reviews could be useful, previous users leaving reviews are typically a selected sample of those who have purchased the good in question, and may consequently have a biased assessment. In this paper, we construct a simple model of dynamic Bayesian learning and profit-maximizing behavior of online platforms to investigate whether such review systems can successfully aggregate past information and the incentives of the…

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The BLOSSOMS – Augmented World Project – Dr. Miri Barak (Israel Institute of Technology)

September 19 @ 3:00 pm - 4:00 pm
MIT Building E18, Room 304, The Ford Building (E18-304)
50 Ames Street, Cambridge, MA 02139 United States
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Technology-enhanced project-based pedagogy for the promotion of scientific thinking

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LIDS Seminar Series: Edmund Yeh (Northeastern University)

September 19 @ 4:00 pm - 5:00 pm
MIT Building 32, Room 141, The Stata Center (32-141)
32 Vassar Street, Cambridge, MA 02139 United States
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