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Emerging Challenges in Deep Learning

Program
Foundations of Deep Learning
Location

Calvin Lab auditorium

Date
Monday, Aug. 5 – Thursday, Aug. 8, 2019
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9 – 9:20 a.m.
Coffee and Check-In
9:20 – 9:30 a.m.
Opening Remarks
9:30 – 10:15 a.m.
Knowledge is embedded in language neural networks but can they reason?
Chris Manning (Stanford University)
10:15 – 11 a.m.
Machine Learning-based Design of Proteins and Small Molecules
Jennifer Listgarten (UC Berkeley)
11 – 11:30 a.m.
Break
11:30 a.m. – 12:15 p.m.
Efficient Deep Learning with Humans in the Loop
Zachary Lipton (Carnegie Mellon University)
12:15 – 2:15 p.m.
Lunch
2:15 – 3 p.m.
Aligning ML objectives with human values
Paul Christiano (US AI Safety Institute)
3 – 3:45 p.m.
Is Deeper Better Only When Shallow Is Good?
Shai Shalev-Shwartz  (The Hebrew University of Jerusalem)
3:45 – 4:15 p.m.
Break
4:15 – 5 p.m.
Flexible Neural Networks and the Frontiers of Meta-Learning
Chelsea Finn (Stanford University)
5 – 6 p.m.
Reception
9 – 9:30 a.m.
Coffee and Check-In
9:30 – 10:15 a.m.
On the Hardness of Reinforcement Learning With Value-function Approximation
Nan Jiang (University of Illinois Urbana-Champaign)
10:15 – 11 a.m.
Reinforcement Learning in Feature Space: Complexity and Regret
Mengdi Wang (Princeton University)
11 – 11:30 a.m.
Break
11:30 a.m. – 12:15 p.m.
Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes
Alekh Agarwal (Microsoft Research Redmond)
12:15 – 2:15 p.m.
Lunch
2:15 – 3 p.m.
Off-policy Policy Optimization
Dale Schuurmans (Google Brain & University of Alberta)
3 – 3:45 p.m.
Reinforcement Learning in Recommender Systems: Some Challenges
Craig Boutilier (Google and University of Toronto)
3:45 – 4:15 p.m.
Break
4:15 – 5 p.m.
Panel
Lihong Li  (Google Brain), Jennifer Listgarten (UC Berkeley), Elchanan Mossel (Massachusetts Institute of Technology), Shai Shalev-Shwartz  (The Hebrew University of Jerusalem), Mengdi Wang (Princeton University), Po-Ling Loh (University of Wisconsin, Madison), Matus Telgarsky (New York University)
9 – 9:30 a.m.
Coffee and Check-In
9:30 – 10:15 a.m.
Reinforcement Learning via an Optimization Lens
Lihong Li (Google Brain)
10:15 – 11 a.m.
Towards Verified Deep Learning
Sanjit Seshia (UC Berkeley)
11 – 11:30 a.m.
Break
11:30 a.m. – 12:15 p.m.
Integrating Constraints into Deep Learning Architectures with Structured Layers
Zico Kolter (CMU Bosch)
12:15 – 2:15 p.m.
Lunch
2:15 – 3 p.m.
The Measure and Mismeasure of Fairness
Sharad Goel (Stanford University)
3 – 3:45 p.m.
Procurement as Policy: Administrative Process For Machine Learning
Deirdre Mulligan (UC Berkeley)
3:45 – 4:15 p.m.
Break
4:15 – 5 p.m.
Panel on Ethics
Sharad Goel (Stanford University), Deirdre Mulligan (UC Berkeley), Emily Witt (Salesforce), Alice Xiang (Partnership on AI), Deirdre Mulligan (UC Berkeley), Matus Telgarsky (New York University)
10:15 – 10:45 a.m.
Coffee and Check-In
10:45 – 11:30 a.m.
Inherent Trade-offs with the Local Explanations Paradigm
Julius Adebayo (MIT)
11:30 a.m. – 12:15 p.m.
How to Fail Interpretability Research
Been Kim (Google Brain)
12:15 – 2:15 p.m.
Lunch
2:15 – 3 p.m.
Better Learning from the Past: Counterfactual / Batch RL
Emma Brunskill (Stanford University)
3 – 3:45 p.m.
Designing Robust Learners
Jacob Steinhardt (Stanford University)
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    • Current Long-Term Visitors
    • Research Fellows
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    • Industry Advisory Council
    • Affiliated Faculty
    • Science Communicators in Residence
    • Law and Society Fellows
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    • Plan Your Visit
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