(17 events)   Timezone: »  
The 2020 schedule is still incomplete Program Highlights »
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Tutorial
Mon Dec 07 12:00 AM -- 02:30 AM (PST)
Deep Conversational AI
Pascale N Fung · Yun-Nung (Vivian) Chen · Zhaojiang Lin · Andrea Madotto
Tutorial
Mon Dec 07 12:00 AM -- 02:30 AM (PST)
Sketching and Streaming Algorithms
Jelani Nelson
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
There and Back Again: A Tale of Slopes and Expectations
Marc Deisenroth · Cheng Soon Ong
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
Designing Learning Dynamics
Marta Garnelo · David Balduzzi · Wojciech Czarnecki
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
Equivariant Networks
Risi Kondor · Taco Cohen
Tutorial
Mon Dec 07 05:30 AM -- 08:00 AM (PST)
Beyond Accuracy: Grounding Evaluation Metrics for Human-Machine Learning Systems
Praveen Chandar · Fernando Diaz · Brian St. Thomas
Tutorial
Mon Dec 07 05:30 AM -- 08:00 AM (PST)
Where Neuroscience meets AI (And What’s in Store for the Future)
Jane Wang · Kevin Miller · Adam H. Marblestone
Tutorial
Mon Dec 07 05:30 AM -- 08:00 AM (PST)
The Beautiful Intertwining of Causal Inference, Experimental Design and Reinforcement Learning
Susan Murphy
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST)
Offline Reinforcement Learning: From Algorithm Design to Practical Applications
Sergey Levine · Aviral Kumar
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST)
Advances in Approximate Inference
Yingzhen Li · Cheng Zhang
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST)
Practical Uncertainty Estimation and Out-of-Distribution Robustness in Deep Learning
Dustin Tran · Balaji Lakshminarayanan · Jasper Snoek
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
Policy Optimization in Reinforcement Learning
Sham M Kakade · Martha White · Nicolas Le Roux
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
Machine Learning for Astrophysics and Astrophysics Problems for Machine Learning
David W Hogg · Kate Storey-Fisher
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
Abstraction & Reasoning in AI systems: Modern Perspectives
Francois Chollet · Melanie Mitchell · Christian Szegedy
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities
Himabindu Lakkaraju · Julius Adebayo · Sameer Singh
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
Federated Learning and Analytics: Industry Meets Academia
Brendan McMahan · Virginia Smith · Peter Kairouz
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
Deep Implicit Layers: Neural ODEs, Equilibrium Models, and Differentiable Optimization
David Duvenaud · J. Zico Kolter · Matthew Johnson