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SILO Seminar Series: Dimitris Papailiopoulos
October 25, 2017 @ 12:30 pm - 1:30 pm
Overcoming the Challenges of Learning in Parallel
Dimitris Papailiopoulos Seminar Video
Distributed implementations of popular machine learning algorithms exhibit poor scaling when deployed on more than a few tens of compute nodes. The key sources of this poor performance are communication bottlenecks and straggler nodes in the system. In this talk, I will explain why these bottlenecks are a real challenge for scaling up, and will provide insights on how to overcome them using simple algebraic ideas. I will show experiments where simple theoretical insights can lead to distributed training algorithms with significant speedup gains, and will conclude with several open problems that lie in the intersection of machine learning and distributed systems.
SILO is a lecture series with speakers from the UW faculty, graduate students or invited researchers that discuss mathematical related topics. The seminars are organized by WID’s Optimization research group.
SILO’s purpose is to provide a forum that helps connect and recruit mathematically-minded graduate students. SILO is a lunch-and-listen format, where speakers present interesting math topics while the audience eats lunch.