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9 Program Highlights »
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Tutorial
Mon Dec 4th 08:00 -- 10:15 AM @ Hall C
Reinforcement Learning with People
Emma Brunskill
Tutorial
Mon Dec 4th 08:00 -- 10:15 AM @ Grand Ballroom
A Primer on Optimal Transport
Marco Cuturi · Justin M Solomon
Tutorial
Mon Dec 4th 08:00 -- 10:15 AM @ Hall A
Deep Learning: Practice and Trends
Nando de Freitas · Scott Reed · Oriol Vinyals
Tutorial
Mon Dec 4th 10:45 AM -- 01:00 PM @ Hall C
Statistical Relational Artificial Intelligence: Logic, Probability and Computation
Luc De Raedt · David Poole · Kristian Kersting · Sriraam Natarajan
Tutorial
Mon Dec 4th 10:45 AM -- 01:00 PM @ Grand Ballroom
Fairness in Machine Learning
Solon Barocas · Moritz Hardt
Tutorial
Mon Dec 4th 10:45 AM -- 01:00 PM @ Hall A
Deep Probabilistic Modelling with Gaussian Processes
Neil D Lawrence
Tutorial
Mon Dec 4th 02:30 -- 04:45 PM @ Hall A
Geometric Deep Learning on Graphs and Manifolds
Michael Bronstein · Joan Bruna · arthur szlam · Xavier Bresson · Yann LeCun
Tutorial
Mon Dec 4th 02:30 -- 04:45 PM @ Hall C
Engineering and Reverse-Engineering Intelligence Using Probabilistic Programs, Program Induction, and Deep Learning
Josh Tenenbaum · Vikash K Mansinghka
Tutorial
Mon Dec 4th 02:30 -- 04:45 PM @ Grand Ballroom
Differentially Private Machine Learning: Theory, Algorithms and Applications
Kamalika Chaudhuri · Anand D Sarwate