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Difference between revisions of "VS265: Reading"

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(Sept 2: Neuron models)
(Sept 4: Linear neuron, Perceptron)
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* [http://redwood.berkeley.edu/vs265/linear-neuron/linear-neuron-models.html Linear neuron models]
 
* [http://redwood.berkeley.edu/vs265/linear-neuron/linear-neuron-models.html Linear neuron models]
 
* [http://redwood.berkeley.edu/vs265/superlearn_handout1.pdf Handout] on supervised learning in single-stage feedforward networks
 
* [http://redwood.berkeley.edu/vs265/superlearn_handout1.pdf Handout] on supervised learning in single-stage feedforward networks
 +
Background on linear algebra:
 
* [http://redwood.berkeley.edu/vs265/linear-algebra/linear-algebra.html Linear algebra primer]
 
* [http://redwood.berkeley.edu/vs265/linear-algebra/linear-algebra.html Linear algebra primer]
 
* Jordan, M.I. [http://redwood.berkeley.edu/vs265/PDP.pdf An Introduction to Linear Algebra in Parallel Distributed Processing] in McClelland and Rumelhart, ''Parallel Distributed Processing'', MIT Press, 1985.
 
* Jordan, M.I. [http://redwood.berkeley.edu/vs265/PDP.pdf An Introduction to Linear Algebra in Parallel Distributed Processing] in McClelland and Rumelhart, ''Parallel Distributed Processing'', MIT Press, 1985.

Revision as of 17:55, 1 September 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

  • HKP chapter 6, DJCM chapters 38-40, 44, DA chapter 8 (sec. 4-6)
  • Linear neuron models
  • Handout on supervised learning in single-stage feedforward networks

Background on linear algebra:




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