Steps Towards`self-referential' Neural Learning: a Thought Experiment

By J. Urgen Schmidhuber. 1992

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Quoc V. Le
2. Sergey Levine
3. Yoshua Bengio
4. Barret Zoph
5. Irwan Bello
6. Mohit Bansal
7. Ruslan Salakhutdinov
8. Trevor Darrell

Citations in the corpus

• Neural Optimizer Search with Reinforcement Learning (2017, methodology): “The concept of using a Recurrent Neural Network for meta-learning has been attempted in the past, either via genetic programming or gradient descent (Schmidhuber, 1992; Hochreiter et al., 2001).”
• Introducing Symmetries to Black Box Meta Reinforcement Learning (2021, background): “…Learning Rules & Fast Weights In the supervised and reinforcement learning contexts, learned learning rules (Bengio et al. 1992) or fast weights (Schmidhuber 1992, 1993a; Miconi, Stanley, and Clune 2018; Schlag, Munkhdalai, and Schmidhuber 2021; Najarro and Risi 2020) describe (meta-)learned…”