Machine Learning Meetup featuring keynote speaker Pedro Domingos

Monday, August 8th

5:30pm - 8:00pm

1191 2nd Avenue, 12th floor

Join the Seattle Machine Learning community for an evening of knowledge sharing and collaboration. Speakers and topics include:

• Keynote: The Five Tribes of Machine Learning, and What You Can Take from Each - Pedro Domingos

• Machine Learning at Uber - Uber Machine Learning Leadership

5:30pm - Doors Open

5:30 - 6:15pm - Food, drinks and networking

6:15 - 7:30pm - Talks

7:30 - 8:00pm - Networking and wrap-up

RSVP required. Please RSVP before Friday, August 5th. Email lkincaid@uber.com with questions.

Keynote abstract: There are five main schools of thought in machine learning,and each has its own master algorithm – a general-purpose learner that can in principle be applied to any domain. The symbolists have inverse deduction, the connectionists have backpropagation, the evolutionaries have genetic programming, the Bayesians have probabilistic inference, and the analogizers have support vector machines. What we really need, however, is a single algorithm combining the key features of all of them. In this talk I will describe my work toward this goal, including in particular Markov logic networks, and speculate on the new applications that such a universal learner will enable, and how society will change as a result.

Pedro Domingos is a professor of the Department of Computer Science & Engineering at the University of Washington. He is a winner of the SIGKDD Innovation Award, the highest honor in data science, a AAAI Fellow, and a recipient of a Sloan Fellowship, a NSF CAREER Award, a Fulbright Scholarship, an IBM Faculty Award, several best paper awards, and other distinctions. He is a member of the editorial board of the Machine Learning journal, co-founder of the International Machine Learning Society, and past associate editor of JAIR. He was program co chair of KDD-2003 and SRL-2009, and he has served on the program committees of AAAI, ICML, IJCAI, KDD, NIPS, SIGMOD, UAI, WWW, and others.