VS265: Slides

27 Aug

• Introduction

29 Aug

• Introduction continued

5 Sept

• Synapses, brains and machines

17/19 Sept

• Supervised learning

24 Sept - 1 Oct

• Unsupervised learning

8 Oct - 15 Oct

• Sparse distributed representation

17 Oct - 22 Oct

• Self-organizing maps
• Manifold models
• (an aside on adaptation)

24 Oct

• Attractor neural networks

29 Oct

• Little-Hopfield Memory Storage with Minimum Probability Flow (Chris Hillar guest lecture)

5 Nov

• Probabilistic/generative models

19 Nov

• Boltzmann machine

21 Nov

• Sparse Coding and 'ICA'