HOME MISSION AND RESEARCH PUBLICATIONS HISTORY PEOPLE SEMINARS COURSES VIDEO ARCHIVE CONTACT

Difference between revisions of "VS265: Reading"

From RedwoodCenter

(21 Oct)
Line 66: Line 66:
 
* [http://cs.brown.edu/people/tld/note/blog/14/10/16/index.html Lecture notes and slides]
 
* [http://cs.brown.edu/people/tld/note/blog/14/10/16/index.html Lecture notes and slides]
  
==== 21 Oct ====
+
==== 21,23,28 Oct ====
 
* Barlow, HB. [http://redwood.berkeley.edu/vs265/barlow1972.pdf Single units and sensation: A neuron doctrine for perceptual psychology?]  Perception, volume 1, pp. 371 -394 (1972)
 
* Barlow, HB. [http://redwood.berkeley.edu/vs265/barlow1972.pdf Single units and sensation: A neuron doctrine for perceptual psychology?]  Perception, volume 1, pp. 371 -394 (1972)
 
* Foldiak, P. [http://redwood.berkeley.edu/vs265/foldiak90.pdf Forming sparse representations by local anti-Hebbian learning]. Biol. Cybern. 64, 165-170 (1990).
 
* Foldiak, P. [http://redwood.berkeley.edu/vs265/foldiak90.pdf Forming sparse representations by local anti-Hebbian learning]. Biol. Cybern. 64, 165-170 (1990).

Revision as of 21:03, 28 October 2014

Aug 28: Introduction

Optional:

Sept 2: Neuron models

Background reading on dynamics, linear time-invariant systems and convolution, and differential equations:

Sept 4: Linear neuron, Perceptron

Background on linear algebra:

Sept 11: Multicompartment models, dendritic integration (Rhodes guest lecture)

Sept. 16, 18: Supervised learning

  • HKP Chapters 5, 6
  • Handout on supervised learning in single-stage feedforward networks
  • Handout on supervised learning in multi-layer feedforward networks - "back propagation"

Further reading:

Sept. 23, 24: Unsupervised learning

  • HKP Chapters 8 and 9, DJCM chapter 36, DA chapter 8, 10
  • Handout: Hebbian learning and PCA
  • PDP Chapter 9 (full text of Michael Jordan's tutorial on linear algebra, including section on eigenvectors)

Optional:

Sept 30, Oct 2: Attractor Networks and Associative Memories (Sommer guest lectures)

  • "HKP" Chapter 2 and 3 (sec. 3.3-3.5), 7 (sec. 7.2-7.3), DJCM chapter 42, DA chapter 7
  • Handout on attractor networks - their learning, dynamics and how they differ from feed-forward networks
  • Hopfield82
  • Hopfield84
  • Willshaw69

Oct 7: Ecological utility and the mythical neural code (Feldman guest lecture)

  • Feldman10 Ecological utility and the mythical neural code

Oct 9: Hyperdimensional computing (Kanerva guest lecture)

Oct 16: Structural and Functional Connectomics (Tom Dean guest lecture)

21,23,28 Oct

Additional readings:

23 Oct

Optional:



Personal tools