October 28–31, 2019

Garrett Lander
Machine Learning Architect, Manceps
Garrett Lander is a machine learning architect at Manceps, an ML consulting agency based out of Portland, Oregon. Garrett works with clients ranging from those taking their first steps into automation to seasoned ML practitioners looking to optimize their production models. Garrett is especially interested in the growing areas of AI pen-tests and ethicality, as well as the effort to build models that improve on human decision making without inheriting its shortcomings.
Sessions
11:50am–12:30pm Thursday, October 31, 2019
Location: Grand Ballroom A/B
Garrett Lander (Manceps),
Al Kari (Manceps)
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Automated investing has brought an immense amount of stability to the market, but it has also brought predictability. Garrett Lander and Al Kari examine if an adversarial network can game the behavior of automated investors by learning the patterns in market activity to which they are most vulnerable.
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