[Ml-stat-talks] Fwd: Reminder: CSML/CS Seminar: Tom Griffiths, January 15, 2016 at 12:30pm | Computer Science, Room 105

Barbara Engelhardt bee at princeton.edu
Wed Jan 13 22:06:39 EST 2016


Talk of interest on Friday.

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Tom Griffiths-University of California, Berkeley

Joint Seminar: CSML/CS

Friday, January 15, 2016

12:30pm-1:30pm

Computer Science, Room 105

**Lunch will be provided**



Title: “Human and machine learning”



Abstract: Human cognition still sets the standard we aspire to in many
areas of machine learning, including problems such as identifying causal
relationships, acquiring and using language, and  learning concepts from a
small number of examples. In these cases, human and machine learning can
establish a mutually beneficial relationship: we can use the formal tools
developed in machine learning to provide insights into human learning, and
translate those insights into new machine learning systems. I will use the
case of causal induction to illustrate the value of this approach, but also
highlight some applications in language and concept learning. I will also
argue that the same kind of mutually beneficial relationship could
potentially exist between developing data-intensive approaches to cognitive
science and making sense of large volumes of behavioral data in computer
science.



If you would like to be added to the CSML listerv, please email
capizzi at princeton.edu.







Joseph D. Capizzi Jr.

Administrative Assistant to the Director

Center for Statistics and Machine Learning

Green Hall, 3-C-5

Princeton University

Princeton, NJ 08544

capizzi at princeton.edu

609-258-9862
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