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VS265: Slides Fall2010

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  • Aug 31 - Intro (cont'd) + neuron models
  • Sep 7 - Supervised learning in single-layer and multilayer networks
  • Sep 21 - Supervised learning - continued
  • Sep 21/23 - Unsupervised learning: Hebbian learning and PCA
  • Sep 28/30 - Sparse distributed representation
  • Oct 5 - Self-organizing maps
  • Oct 7 - Manifold models
  • Oct 12/14 - Attractor neural networks
  • Oct 19 - Recurrent networks and dynamical systems - (David Zipser)
  • Oct 21 - Associative memory models (Fritz Sommer)
  • Oct 26/28 - Probabilistic/generative models
  • Nov 4/9 - Boltzmann machines
  • Nov 16 - ICA and sparse coding
  • Nov 18 - Kalman filter
  • Nov 23 - Spiking neurons
  • Nov 30 - Computation and coding with neural assemblies (Kilian Koepsell)
  • Dec 2 - Hierarchical temporal memory (Jeff Hawkins)
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