| 2:00 - 2:20 | Jürgen Schmidhuber
Introduction to Recurrent Neural Networks and Other Machines that Learn Algorithms
Slides Video |
| 2:20 - 2:40 | Paul Werbos
Deep Learning in Recurrent Networks: From Basics To New Data on the Brain
Slides Video |
| 2:40 - 3:00 | Li Deng
Three Cool Topics on RNN
Slides Video |
| 3:00 - 3:20 | Risto Miikkulainen
Scaling Up Deep Learning through Neuroevolution
Slides Video |
| 3:20 - 3:40 | Jason Weston
New Tasks and Architectures for Language Understanding and Dialogue with Memory
Slides Video |
| 3:40 - 4:00 | Oriol Vinyals
Recurrent Nets Frontiers
Slides Unavailable Video |
| |
| 4:00 - 4:30 | Coffee Break |
| |
| 4:30 - 4:50 | Mike Mozer
Neural Hawkes Process Memories
Slides Video |
| 4:50 - 5:10 | Ilya Sutskever
Meta Learning in the Universe
Slides Video |
| 5:10 - 5:30 | Marcus Hutter
Asymptotically fastest solver of all well-defined problems
Slides Video |
| | (unfortunately cannot come - J. Schmidhuber will stand in for him) |
| 5:30 - 5:50 | Nando de Freitas
Learning to Learn, to Program, to Explore and to Seek Knowledge
Slides Video |
| 5:50 - 6:10 | Alex Graves
Differentiable Neural Computer
Slides Video |
| |
| 6:30 - 7:30 | Light dinner break/Posters |
| |
| 7:30 - 7:50 | Nal Kalchbrenner
Generative Modeling as Sequence Learning
Slides Video |
| 7:50 - 9:00 | Panel Discussion
Topic: The future of machines that learn algorithms
Panelists: Ilya Sutskever, Jürgen Schmidhuber, Li Deng, Paul Werbos, Risto Miikkulainen, Sepp Hochreiter
Moderator: Alex Graves
Video |
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