VS265: Slides Fall2010: Difference between revisions
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* '''Nov 4/9 - Boltzmann machines''' | * '''Nov 4/9 - Boltzmann machines''' | ||
**[http://redwood.berkeley.edu/vs265/boltzmann-machine-slides.pdf slides] | **[http://redwood.berkeley.edu/vs265/boltzmann-machine-slides.pdf slides] | ||
* '''Nov 16 - ICA and sparse coding''' | |||
**[http://redwood.berkeley.edu/vs265/sparse-coding2-slides.pdf slides] | |||
* '''Nov 18 - Kalman filter''' | |||
**[http://redwood.berkeley.edu/vs265/kalman-slides.pdf slides] | |||
* '''Nov 23 - Spiking neurons''' | |||
**[http://redwood.berkeley.edu/vs265/spikes-slides.pdf slides] | |||
* '''Nov 30 - Computation and coding with neural assemblies (Kilian Koepsell)''' | |||
**[http://redwood.berkeley.edu/vs265/kilian-lecture.pdf slides] | |||
* '''Dec 2 - Hierarchical temporal memory (Jeff Hawkins)''' | |||
**[http://redwood.berkeley.edu/vs265/Hawkins-lecture.pptx slides] | |||
Latest revision as of 02:44, 28 August 2012
- Aug 26 - Introduction
- 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 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)
