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Is backpropagation the ultimate tool on the path to achieving synthetic intelligence as its success and widespread adoption would suggest?
Many have questioned the biological plausibility of backpropagation as a learning mechanism since its discovery. The weight transport and timing problems are the most disputable. The same properties of backpropagation training also have practical consequences. For instance, backpropagation training is a global and coupled procedure that limits the amount of possible parallelism and yields high latency.
These limitations have motivated us to discuss possible alternative directions. In this workshop, we want to promote such discussions by bringing together researchers from various but related disciplines, and to discuss possible solutions from engineering, machine learning and neuroscientific perspectives.
Sat 6:00 a.m. - 6:15 a.m.
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Live Intro
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Talk
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Mateusz Malinowski · Viorica Patraucean · Grzegorz Swirszcz · Sindy Löwe · Anna Choromanska · Marco Gori · Yanping Huang 🔗 |
Sat 6:15 a.m. - 6:17 a.m.
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Introduction: Bastiaan Veeling
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Introduction
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Mateusz Malinowski 🔗 |
Sat 6:17 a.m. - 6:45 a.m.
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Invited Talk Bastiaan Veeling
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Talk
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SlidesLive Video » |
Bas Veeling 🔗 |
Sat 6:45 a.m. - 6:47 a.m.
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Introduction: Olivier Teytaud
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Introduction
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Sindy Löwe 🔗 |
Sat 6:47 a.m. - 7:15 a.m.
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Invited Talk Olivier Teytaud
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Talk
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SlidesLive Video » |
Olivier Teytaud 🔗 |
Sat 7:15 a.m. - 8:30 a.m.
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Poster Session: Morning ( Parallel poster session ) link » | 🔗 |
Sat 8:30 a.m. - 8:32 a.m.
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Introduction: Karl Friston
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Introduction
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Mateusz Malinowski 🔗 |
Sat 8:32 a.m. - 9:00 a.m.
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Invited Talk Karl Friston
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Talk
)
SlidesLive Video » |
Karl Friston 🔗 |
Sat 9:00 a.m. - 9:45 a.m.
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Panel discussion 1
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Discussion
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Bas Veeling · Olivier Teytaud · Karl Friston · Sindy Löwe · Mateusz Malinowski 🔗 |
Sat 9:45 a.m. - 11:00 a.m.
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Long Break
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🔗 |
Sat 11:00 a.m. - 11:02 a.m.
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Introduction: Yoshua Bengio
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Introduction
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Anna Choromanska 🔗 |
Sat 11:02 a.m. - 11:32 a.m.
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Invited Talk Yoshua Bengio
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Talk
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SlidesLive Video » |
Yoshua Bengio 🔗 |
Sat 11:32 a.m. - 11:34 a.m.
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Introduction: Danielle Bassett
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Introduction
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Anna Choromanska 🔗 |
Sat 11:34 a.m. - 12:08 p.m.
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Invited Talk Danielle Bassett
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Talk
)
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Danielle S Bassett 🔗 |
Sat 12:09 p.m. - 12:10 p.m.
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Introduction: Oral 1.1 and Oral 1.2
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Introduction
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Viorica Patraucean 🔗 |
Sat 12:10 p.m. - 12:22 p.m.
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Orals 1.1: Randomized Automatic Differentiation
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Contributed Talks
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SlidesLive Video » |
Deniz Oktay · Nick McGreivy · Alex Beatson · Ryan Adams 🔗 |
Sat 12:22 p.m. - 12:35 p.m.
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Orals 1.2: ZORB: A Derivative-Free Backpropagation Algorithm for Neural Networks
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Contributed Talks
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SlidesLive Video » |
Varun Ranganathan · Alex Lewandowski 🔗 |
Sat 12:35 p.m. - 12:40 p.m.
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Oral 1.1 and 1.2 Q&A
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Q&A
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🔗 |
Sat 12:40 p.m. - 12:45 p.m.
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Short Break 2
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🔗 |
Sat 12:45 p.m. - 12:46 p.m.
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Introduction: Oral 2.1 and Oral 2.2
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Introduction
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Viorica Patraucean 🔗 |
Sat 12:46 p.m. - 12:59 p.m.
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Orals 2.1: Policy Manifold Search for Improving Diversity-based Neuroevolution
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Contributed Talks
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SlidesLive Video » |
Nemanja Rakicevic 🔗 |
Sat 12:59 p.m. - 1:12 p.m.
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Orals 2.2: Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignmen
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Contributed Talks
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SlidesLive Video » |
Julien Launay · Iacopo Poli · Laurent Daudet · Florent Krzakala 🔗 |
Sat 1:12 p.m. - 1:15 p.m.
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Oral 2.1 and Oral 2.2 Q&A
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Q&A
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🔗 |
Sat 1:15 p.m. - 1:17 p.m.
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Introduction: David Duvenaud
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Introduction
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Yanping Huang 🔗 |
Sat 1:17 p.m. - 1:45 p.m.
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Invited Talk David Duvenaud
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Talk
)
SlidesLive Video » |
David Duvenaud 🔗 |
Sat 1:45 p.m. - 1:47 p.m.
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Introduction: Cristina Savin
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Introduction
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Yanping Huang 🔗 |
Sat 1:47 p.m. - 2:15 p.m.
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Invited Talk Cristina Savin
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Talk
)
SlidesLive Video » |
Cristina Savin 🔗 |
Sat 2:15 p.m. - 3:00 p.m.
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Panel discussion 2
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Discussion
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Danielle S Bassett · Yoshua Bengio · Cristina Savin · David Duvenaud · Anna Choromanska · Yanping Huang 🔗 |
Sat 3:00 p.m. - 4:30 p.m.
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Poster Session: Evening ( Posters ) link » | 🔗 |
Author Information
Mateusz Malinowski (DeepMind)
Mateusz Malinowski is a research scientist at DeepMind, where he works at the intersection of computer vision, natural language understanding, and deep learning. He was granted PhD (Dr.-Ing.) with the highest honor (summa cum laude) at Max Planck Institute for Informatics in 2017 in computer vision for his pioneering work on visual question answering, where he proposed the task and developed methods that answer questions about the content of images. Prior to this, he graduated with honors from Saarland University in computer science. Before that, he studied computer science at Wroclaw University in Poland.
Grzegorz Swirszcz (DeepMind)
Viorica Patraucean (DeepMind)
Marco Gori (University of Siena)
Yanping Huang (Google Brain)
Sindy Löwe (University of Amsterdam)
Anna Choromanska (NYU Tandon School of Engineering)
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