Implications of Recursive Distributed Representations

By Jordan B. Pollack. 1988

How researchers see this paper

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

1. J. Urgen Schmidhuber
2. David R Ha
3. Yoshua Bengio
4. Sergey Levine
5. Quoc V. Le
6. Chelsea Finn
7. Alex Graves
8. Trevor Darrell

Citations in the corpus

• Deep learning in neural networks: An overview (2014, methodology): “suka, 2010), and a RAAM (Pollack, 1988) (Section 5.”
• On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models (2015, methodology): “A RAAM RNN [193] was employed as a deep unsupervised sequence encoder for RL [65].”
• Recursive Distributed Representations (1990, background): “memories with fractal dimensions are further discussed elsewhere [ 36 ].”
• My First Deep Learning System of 1991 + Deep Learning Timeline 1962-2013 (2013, background): “In 1987, Ballard published ideas on unsupervised autoencoder hierarchies [7], related to post-2000 feed-forward Deep Learners (TL 1.9) based on unsupervised pre-training, e.g., [44]; compare survey [45] and somewhat related RAAMs [69].”