(30 events)   Timezone: »  
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Tutorial
Mon Dec 07 12:00 AM -- 02:30 AM (PST)
(Track1) Sketching and Streaming Algorithms
Jelani Nelson
Tutorial
Mon Dec 07 12:00 AM -- 02:30 AM (PST) @ Virtual
(Track2) Deeper Conversational AI
Pascale N Fung · Yun-Nung (Vivian) Chen · Zhaojiang Lin · Andrea Madotto
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
(Track3) Designing Learning Dynamics
Marta Garnelo · David Balduzzi · Wojciech Czarnecki
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
(Track2) Equivariant Networks
Risi Kondor · Taco Cohen
Tutorial
Mon Dec 07 02:30 AM -- 05:00 AM (PST)
(Track1) There and Back Again: A Tale of Slopes and Expectations
Marc Deisenroth · Cheng Soon Ong
Tutorial
Mon Dec 07 05:30 AM -- 08:00 AM (PST)
(Track2) 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)
(Track1) Where Neuroscience meets AI (And What’s in Store for the Future)
Jane Wang · Kevin Miller · Adam H. Marblestone
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST) @ Virtual
(Track2) Practical Uncertainty Estimation and Out-of-Distribution Robustness in Deep Learning
Dustin Tran · Balaji Lakshminarayanan · Jasper Snoek
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST)
(Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications
Sergey Levine · Aviral Kumar
Tutorial
Mon Dec 07 08:00 AM -- 10:30 AM (PST) @ Virtual
(Track1) Advances in Approximate Inference
Yingzhen Li · Cheng Zhang
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
(Track1) Abstraction & Reasoning in AI systems: Modern Perspectives
Francois Chollet · Melanie Mitchell · Christian Szegedy
Tutorial
Mon Dec 07 11:00 AM -- 01:30 PM (PST)
(Track2) 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)
(Track3) Policy Optimization in Reinforcement Learning
Sham M Kakade · Martha White · Nicolas Le Roux
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
(Track1) Federated Learning and Analytics: Industry Meets Academia
Brendan McMahan · Virginia Smith · Peter Kairouz
Tutorial
Mon Dec 07 01:30 PM -- 04:00 PM (PST)
(Track2) 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)
(Track3) Deep Implicit Layers: Neural ODEs, Equilibrium Models, and Differentiable Optimization
David Duvenaud · J. Zico Kolter · Matthew Johnson
Tutorial
Tue Dec 08 02:00 AM -- 02:50 AM (PST)
(Track2) Equivariant Networks Q&A
Risi Kondor · Taco Cohen
Tutorial
Tue Dec 08 03:00 AM -- 03:50 AM (PST)
(Track1) There and Back Again: A Tale of Slopes and Expectations Q&A
Marc Deisenroth · Cheng Soon Ong
Tutorial
Tue Dec 08 12:00 PM -- 12:50 PM (PST)
(Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications Q&A
Sergey Levine · Aviral Kumar
Tutorial
Tue Dec 08 01:00 PM -- 01:50 PM (PST)
(Track1) Sketching and Streaming Algorithms Q&A
Jelani Nelson
Tutorial
Tue Dec 08 02:00 PM -- 02:50 PM (PST)
(Track2) Beyond Accuracy: Grounding Evaluation Metrics for Human-Machine Learning Systems Q&A
Praveen Chandar · Fernando Diaz · Brian St. Thomas
Tutorial
Wed Dec 09 01:00 AM -- 01:50 AM (PST)
(Track1) Advances in Approximate Inference Q&A
Yingzhen Li · Cheng Zhang
Tutorial
Wed Dec 09 03:00 AM -- 03:50 AM (PST)
(Track2) Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities Q&A
Himabindu Lakkaraju · Julius Adebayo · Sameer Singh
Tutorial
Wed Dec 09 12:00 PM -- 12:50 PM (PST)
(Track2) Practical Uncertainty Estimation and Out-of-Distribution Robustness in Deep Learning Q&A
Dustin Tran · Balaji Lakshminarayanan · Jasper Snoek
Tutorial
Wed Dec 09 02:00 PM -- 02:50 PM (PST)
(Track1) Abstraction & Reasoning in AI systems: Modern Perspectives Q&A
Francois Chollet · Melanie Mitchell · Christian Szegedy
Tutorial
Thu Dec 10 12:00 AM -- 12:50 AM (PST)
(Track2) Deep Conversational AI Q&A
Pascale N Fung · Yun-Nung (Vivian) Chen · Zhaojiang Lin · Andrea Madotto
Tutorial
Thu Dec 10 02:00 AM -- 02:50 AM (PST)
(Track3) Designing Learning Dynamics Q&A
Marta Garnelo · David Balduzzi · Wojciech Czarnecki
Tutorial
Thu Dec 10 03:00 AM -- 03:50 AM (PST)
(Track3) Deep Implicit Layers: Neural ODEs, Equilibrium Models, and Differentiable Optimization Q&A
David Duvenaud · J. Zico Kolter · Matthew Johnson
Tutorial
Thu Dec 10 12:00 PM -- 12:50 PM (PST)
(Track1) Federated Learning and Analytics: Industry Meets Academia Q&A
Peter Kairouz · Brendan McMahan · Virginia Smith
Tutorial
Thu Dec 10 01:00 PM -- 01:50 PM (PST)
(Track3) Policy Optimization in Reinforcement Learning Q&A
Sham M Kakade · Martha White · Nicolas Le Roux