# Difference between revisions of "VS265: Reading Fall2010"

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==== 28 Sep ==== | ==== 28 Sep ==== | ||

− | * Foldiak, P. [http://redwood.berkeley.edu/ | + | * Foldiak, P. [http://redwood.berkeley.edu/vs265/foldiak90.pdf Forming sparse representations by local anti-Hebbian learning]. Biol. Cybern. 64, 165-170 (1990). |

* Olshausen BA, Field DJ. [http://redwood.berkeley.edu/amir/vs298/bruno-nature.pdf Emergence of simple-cell receptive field properties by learning a sparse code for natural images], Nature, 381: 607-609. (1996) | * Olshausen BA, Field DJ. [http://redwood.berkeley.edu/amir/vs298/bruno-nature.pdf Emergence of simple-cell receptive field properties by learning a sparse code for natural images], Nature, 381: 607-609. (1996) | ||

Optional readings: | Optional readings: | ||

− | * Rozell, Johnson, Baraniuk, Olshausen. [http://redwood.berkeley.edu/ | + | * Rozell, Johnson, Baraniuk, Olshausen. [http://redwood.berkeley.edu/vs265/rozell-sparse-coding-nc08.pdf Sparse Coding via Thresholding and Local Competition in Neural Circuits], Neural Computation 20, 2526–2563 (2008). |

− | * Simoncelli, Olshausen. [http://redwood.berkeley.edu/ | + | * Simoncelli, Olshausen. [http://redwood.berkeley.edu/vs265/simoncelli01-reprint.pdf Natural Image Statistics and Neural Representation], Annu. Rev. Neurosci. 2001. 24:1193–216. |

− | * Smith, Lewicki. [http://redwood.berkeley.edu/ | + | * Smith, Lewicki. [http://redwood.berkeley.edu/vs265/smith-lewicki-nature06.pdf Efficient auditory coding], Nature Vol 439 (2006). |

<!--A handout on sparse coding and on 'ICA', something we haven't yet discussed: | <!--A handout on sparse coding and on 'ICA', something we haven't yet discussed: | ||

− | * [http://redwood.berkeley.edu/ | + | * [http://redwood.berkeley.edu/vs265/sparse-coding-handout.pdf Sparse coding and 'ICA' ]--> |

<!--Dayan and Abbott has a nice section on sparse coding in Chapter 10. This is on the syllabus for unsupervised learning already, but you may want to focus on section 10.3 and 10.4.--> | <!--Dayan and Abbott has a nice section on sparse coding in Chapter 10. This is on the syllabus for unsupervised learning already, but you may want to focus on section 10.3 and 10.4.--> | ||

<!--Here is a link to [http://www.dsp.ece.rice.edu/cs/ Compressive Sensive Resources] at Rice. It has an enormous number of recent papers related to compressed sensing and sparse coding.--> | <!--Here is a link to [http://www.dsp.ece.rice.edu/cs/ Compressive Sensive Resources] at Rice. It has an enormous number of recent papers related to compressed sensing and sparse coding.--> |

## Revision as of 21:33, 28 September 2010

#### 26 Aug

- Dreyfus, H.L. and Dreyfus, S.E.
*Making a Mind vs. Modeling the Brain: Artificial Intelligence Back at a Branchpoint*. Daedalus, Winter 1988. - Bell, A.J.
*Levels and loops: the future of artificial intelligence and neuroscience*. Phil Trans: Bio Sci.**354**:2013--2020 (1999) here or here

Optional:

- Land, MF and Fernald, RD. The Evolution of Eyes, Ann Revs Neuro, 1992.

#### 31 Aug

- Mead, C. Chapter 1: Introduction and Chapter 4: Neurons from
*Analog VLSI and Neural Systems*, Addison-Wesley, 1989. - Linear time-invariant systems and convolution
- Simulating differential equations
- Dynamics
- Carandini M, Heeger D (1994) Summation and division by neurons in primate visual cortex. Science, 264: 1333-1336.

#### 02 Sep

- Jordan, M.I. An Introduction to Linear Algebra in Parallel Distributed Processing in McClelland and Rumelhart,
*Parallel Distributed Processing*, MIT Press, 1985. - Linear neuron models
- Linear algebra primer

#### 07 Sep

- Handout on supervised learning in single-stage feedforward networks
- Handout on supervised learning in multi-layer feedforward networks - "backpropagation"
- Y. LeCun, L. Bottou, G. Orr, and K. Muller (1998) "Efficient BackProp," in Neural Networks: Tricks of the trade, (G. Orr and Muller K., eds.).
- NetTalk demo

#### 21 Sep

- Handout: Hebbian learning and PCA
**HKP**Chapters 8 and 9**PDP**Chapter 9 (full text of Michael Jordan's tutorial on linear algebra, including section on eigenvectors)

Optional:

- Atick, Redlich. What does the retina know about natural scenes?, Neural Computation, 1992.
- Dan, Atick, Reid. Efficient Coding of Natural Scenes in the Lateral Geniculate Nucleus: Experimental Test of a Computational Theory, J Neuroscience, 1996.

#### 28 Sep

- Foldiak, P. Forming sparse representations by local anti-Hebbian learning. Biol. Cybern. 64, 165-170 (1990).
- Olshausen BA, Field DJ. Emergence of simple-cell receptive field properties by learning a sparse code for natural images, Nature, 381: 607-609. (1996)

Optional readings:

- Rozell, Johnson, Baraniuk, Olshausen. Sparse Coding via Thresholding and Local Competition in Neural Circuits, Neural Computation 20, 2526–2563 (2008).
- Simoncelli, Olshausen. Natural Image Statistics and Neural Representation, Annu. Rev. Neurosci. 2001. 24:1193–216.
- Smith, Lewicki. Efficient auditory coding, Nature Vol 439 (2006).