Difference between revisions of "VS298: Reading"

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For each lecture, we also have a list of optional reading corresponding to ideas discussed in lecture. You may read these if you are interested in the particular topic: [http://redwood.berkeley.edu/wiki/VS298:_Optional_Reading Optional Reading]
 
 
 
==== 2 Sep ====
 
==== 2 Sep ====
  
 
* Bell, A.J. ''Levels and loops: the future of artificial intelligence and neuroscience''. Phil Trans: Bio Sci. '''354''':2013--2020 (1999) [http://dx.doi.org/10.1098/rstb.1999.0540 here] or [http://www.cnl.salk.edu/~tony/ptrsl.pdf here]
 
* Bell, A.J. ''Levels and loops: the future of artificial intelligence and neuroscience''. Phil Trans: Bio Sci. '''354''':2013--2020 (1999) [http://dx.doi.org/10.1098/rstb.1999.0540 here] or [http://www.cnl.salk.edu/~tony/ptrsl.pdf here]
* Dreyfus, H.L. and Dreyfus, S.E. [http://connes.berkeley.edu/~amir/vs298/DreyfusDreyfus.pdf ''Making a Mind vs. Modeling the Brain: Artificial Intelligence Back at a Branchpoint'']. Daedalus, Winter 1988.
+
* Dreyfus, H.L. and Dreyfus, S.E. [http://redwood.berkeley.edu/amir/vs298/DreyfusDreyfus.pdf ''Making a Mind vs. Modeling the Brain: Artificial Intelligence Back at a Branchpoint'']. Daedalus, Winter 1988.
* Mead, C. [http://connes.berkeley.edu/~amir/vs298/Mead.pdf Chapter 1: Introduction] and [http://connes.berkeley.edu/~amir/vs298/Neurons.pdf Chapter 4: Neurons] from ''Analog VLSI and Neural Systems'', Addison-Wesley, 1989.
+
* Mead, C. [http://redwood.berkeley.edu/amir/vs298/Mead.pdf Chapter 1: Introduction] and [http://redwood.berkeley.edu/amir/vs298/Neurons.pdf Chapter 4: Neurons] from ''Analog VLSI and Neural Systems'', Addison-Wesley, 1989.
* Jordan, M.I. [http://connes.berkeley.edu/~amir/vs298/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/amir/vs298/PDP.pdf An Introduction to Linear Algebra in Parallel Distributed Processing] in McClelland and Rumelhart, ''Parallel Distributed Processing'', MIT Press, 1985.
* Zhang K, Sejnowski TJ (2000)  [http://connes.berkeley.edu/~amir/vs298/zhang-sejnowski.pdf A universal scaling law between gray matter and white matter of cerebral cortex.]  PNAS, 97: 5621–5626.
+
* Zhang K, Sejnowski TJ (2000)  [http://redwood.berkeley.edu/amir/vs298/zhang-sejnowski.pdf A universal scaling law between gray matter and white matter of cerebral cortex.]  PNAS, 97: 5621–5626.
 +
 
 +
Optional:
 +
 
 +
* Land, MF and Fernald, RD. [http://connes.berkeley.edu/~amir/vs298/landfernald92.pdf The Evolution of Eyes], Ann Revs Neuro, 1992.
 +
 
 +
* Douglas, R and Martin, K. [http://connes.berkeley.edu/~amir/vs298/douglasmartin2007.pdf Recurrent neuronal circuits in the neocortex], Current Biology, 2007.
  
 
==== 04 Sep ====
 
==== 04 Sep ====
* [http://connes.berkeley.edu/~amir/vs298/linear-neuron/linear-neuron-models.html Linear neuron models]
+
* [http://redwood.berkeley.edu/amir/vs298/linear-neuron/linear-neuron-models.html Linear neuron models]
* [http://connes.berkeley.edu/~amir/vs298/lti-conv/lti-convolution.html Linear time-invariant systems and convolution]
+
* [http://redwood.berkeley.edu/amir/vs298/lti-conv/lti-convolution.html Linear time-invariant systems and convolution]
* [http://connes.berkeley.edu/~amir/vs298/diffeq-sim/diffeq-sim.html Simulating differential equations]
+
* [http://redwood.berkeley.edu/amir/vs298/diffeq-sim/diffeq-sim.html Simulating differential equations]
* Carandini M, Heeger D (1994) [http://connes.berkeley.edu/~amir/vs298/carandini-heeger.pdf Summation and division by neurons in primate visual cortex.]  Science, 264: 1333-1336.
+
* Carandini M, Heeger D (1994) [http://redwood.berkeley.edu/amir/vs298/carandini-heeger.pdf Summation and division by neurons in primate visual cortex.]  Science, 264: 1333-1336.
 
Optional reading for more background:
 
Optional reading for more background:
* [http://connes.berkeley.edu/~amir/vs298/linear-algebra/linear-algebra.html Linear algebra primer]
+
* [http://redwood.berkeley.edu/amir/vs298/linear-algebra/linear-algebra.html Linear algebra primer]
* [http://connes.berkeley.edu/~amir/vs298/dynamics/dynamics.html Dynamics]
+
* [http://redwood.berkeley.edu/amir/vs298/dynamics/dynamics.html Dynamics]
  
 
==== 16 Sep ====
 
==== 16 Sep ====
* [http://connes.berkeley.edu/~amir/vs298/superlearn1.pdf Handout] on supervised learning in single-stage feedforward networks
+
* [http://redwood.berkeley.edu/amir/vs298/superlearn1.pdf Handout] on supervised learning in single-stage feedforward networks
  
 
==== 18 Sep ====
 
==== 18 Sep ====
* [http://connes.berkeley.edu/~amir/vs298/superlearn2.pdf Handout] on supervised learning in multi-layer feedforward networks - "backpropagation"
+
* [http://redwood.berkeley.edu/amir/vs298/superlearn2.pdf Handout] on supervised learning in multi-layer feedforward networks - "backpropagation"
* Y. LeCun, L. Bottou, G. Orr, and K. Muller (1998) [http://connes.berkeley.edu/~amir/vs298/lecun-98b.pdf  "Efficient BackProp,"]  in Neural Networks: Tricks of the trade, (G. Orr and Muller K., eds.).
+
* Y. LeCun, L. Bottou, G. Orr, and K. Muller (1998) [http://redwood.berkeley.edu/amir/vs298/lecun-98b.pdf  "Efficient BackProp,"]  in Neural Networks: Tricks of the trade, (G. Orr and Muller K., eds.).
 
* [http://www.cnl.salk.edu/ParallelNetsPronounce/index.php NetTalk demo]
 
* [http://www.cnl.salk.edu/ParallelNetsPronounce/index.php NetTalk demo]
  
 
==== 23 Sep ====
 
==== 23 Sep ====
* Handout: [http://connes.berkeley.edu/~amir/vs298/hebb-pca.pdf Hebbian learning and PCA]
+
* Handout: [http://redwood.berkeley.edu/amir/vs298/hebb-pca.pdf Hebbian learning and PCA]
 
* '''HKP''' Chapter 8
 
* '''HKP''' Chapter 8
* '''PDP''' [http://connes.berkeley.edu/~amir/vs298/chap9.pdf Chapter 9] (full text of Michael Jordan's tutorial on linear algebra, including section on eigenvectors)
+
* '''PDP''' [http://redwood.berkeley.edu/amir/vs298/chap9.pdf Chapter 9] (full text of Michael Jordan's tutorial on linear algebra, including section on eigenvectors)
  
 
==== 25 Sep ====
 
==== 25 Sep ====
 
* '''HKP''' Chapter 9
 
* '''HKP''' Chapter 9
 +
 +
Optional:
 +
 +
* Atick, Redlich. [http://connes.berkeley.edu/~amir/vs298/Atick-Redlich-NC92.pdf What does the retina know about natural scenes?], Neural Computation, 1992.
 +
 +
* Dan, Atick, Reid. [http://www.jneurosci.org/cgi/reprint/16/10/3351.pdf Efficient Coding of Natural Scenes in the Lateral Geniculate Nucleus: Experimental Test of a Computational Theory], J Neuroscience, 1996.
  
 
==== 30 Sep ====
 
==== 30 Sep ====
* Foldiak, P. [http://connes.berkeley.edu/~amir/vs298/foldiak90.pdf Forming sparse representations by local anti-Hebbian learning]. Biol. Cybern. 64, 165-170 (1990).
+
* Foldiak, P. [http://redwood.berkeley.edu/amir/vs298/foldiak90.pdf Forming sparse representations by local anti-Hebbian learning]. Biol. Cybern. 64, 165-170 (1990).
* Olshausen BA, Field DJ. [http://connes.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)
  
 
==== 2 Oct ====
 
==== 2 Oct ====
 
Optional readings that covers material in lecture in greater depth:
 
Optional readings that covers material in lecture in greater depth:
  
* Rozell, Johnson, Baraniuk, Olshausen. [http://connes.berkeley.edu/~amir/vs298/rozell-sparse-coding-nc08.pdf Sparse Coding via Thresholding and Local Competition in Neural Circuits], Neural Computation 20, 2526–2563 (2008).
+
* Rozell, Johnson, Baraniuk, Olshausen. [http://redwood.berkeley.edu/amir/vs298/rozell-sparse-coding-nc08.pdf Sparse Coding via Thresholding and Local Competition in Neural Circuits], Neural Computation 20, 2526–2563 (2008).
  
* Simoncelli, Olshausen. [http://connes.berkeley.edu/~amir/vs298/simoncelli01-reprint.pdf Natural Image Statistics and Neural Representation], Annu. Rev. Neurosci. 2001. 24:1193–216.
+
* Simoncelli, Olshausen. [http://redwood.berkeley.edu/amir/vs298/simoncelli01-reprint.pdf Natural Image Statistics and Neural Representation], Annu. Rev. Neurosci. 2001. 24:1193–216.
  
* Smith, Lewicki. [http://connes.berkeley.edu/~amir/vs298/smith-lewicki-nature06.pdf Efficient auditory coding], Nature Vol 439 (2006).
+
* Smith, Lewicki. [http://redwood.berkeley.edu/amir/vs298/smith-lewicki-nature06.pdf Efficient auditory coding], Nature Vol 439 (2006).
  
 
==== 7 Oct ====
 
==== 7 Oct ====
 
+
<!--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/amir/vs298/sparse-coding-handout.pdf Sparse coding and 'ICA' ]-->
* [http://connes.berkeley.edu/~amir/vs298/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.
Line 58: Line 67:
 
==== 9 Oct ====
 
==== 9 Oct ====
  
Here are a list of references for David Zipser's talk: [http://connes.berkeley.edu/~amir/vs298/backpropneuralref.pdf pdf]. David also suggested the following chapter in an upcoming book by Thomas J. Anastasio: [http://connes.berkeley.edu/~amir/vs298/zipserchap10.pdf pdf (waiting for approval to post)]
+
Here are a list of references for David Zipser's talk: [http://redwood.berkeley.edu/amir/vs298/backpropneuralref.pdf pdf]. David also suggested the following chapter in an upcoming book by Thomas J. Anastasio: [http://redwood.berkeley.edu/amir/vs298/zipserchap10.pdf pdf (waiting for approval to post)]
  
 
==== 14 Oct ====
 
==== 14 Oct ====
  
* [http://connes.berkeley.edu/~amir/vs298/miller89.pdf Ocular dominance column development: Analysis and simulation] by Miller, Keller and Stryker.
+
* [http://redwood.berkeley.edu/amir/vs298/miller89.pdf Ocular dominance column development: Analysis and simulation] by Miller, Keller and Stryker.
* [http://connes.berkeley.edu/~amir/vs298/durbin-mitchison.pdf A dimension reduction framework for understanding cortical maps] by R. Durbin and G. Mitchison.
+
* [http://redwood.berkeley.edu/amir/vs298/durbin-mitchison.pdf A dimension reduction framework for understanding cortical maps] by R. Durbin and G. Mitchison.
* [http://connes.berkeley.edu/~amir/vs298/horton05.pdf The cortical column: a structure without a function] by Jonathan C. Horton and Daniel L. Adams
+
* [http://redwood.berkeley.edu/amir/vs298/horton05.pdf The cortical column: a structure without a function] by Jonathan C. Horton and Daniel L. Adams
  
 
Here are some additional links to papers mentioned in lecture. Optional reading:
 
Here are some additional links to papers mentioned in lecture. Optional reading:
  
- Gary Blasdel, [http://connes.berkeley.edu/~amir/vs298/blasdel1992.pdf Differential Imaging of Ocular Dominance and Orientation Selectivity in Monkey Striate Cortex], J Neurosci, 1992.  Another source of many of nice images are in the galleries on Amiram Grinvald's site: [http://www.weizmann.ac.il/brain/grinvald/]
+
- Gary Blasdel, [http://redwood.berkeley.edu/amir/vs298/blasdel1992.pdf Differential Imaging of Ocular Dominance and Orientation Selectivity in Monkey Striate Cortex], J Neurosci, 1992.  Another source of many of nice images are in the galleries on Amiram Grinvald's site: [http://www.weizmann.ac.il/brain/grinvald/]
  
 
- From Clay Reid's lab, [http://www.nature.com/nature/journal/v433/n7026/abs/nature03274.html Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex]. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [http://reid.med.harvard.edu/movies.html].
 
- From Clay Reid's lab, [http://www.nature.com/nature/journal/v433/n7026/abs/nature03274.html Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex]. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [http://reid.med.harvard.edu/movies.html].
Line 74: Line 83:
 
==== 16 Oct ====
 
==== 16 Oct ====
  
* [http://connes.berkeley.edu/~amir/vs298/tenenbaum-manifold.pdf A Global Geometric Framework for Nonlinear Dimensionality Reduction ], Tenenbaum et al., Science 2000.
+
* [http://redwood.berkeley.edu/amir/vs298/tenenbaum-manifold.pdf A Global Geometric Framework for Nonlinear Dimensionality Reduction ], Tenenbaum et al., Science 2000.
  
* [http://connes.berkeley.edu/~amir/vs298/roweis-saul-manifold.pdf Nonlinear Dimensionality Reduction by Locally Linear Embedding], Roweis and Saul, Science 2000.
+
* [http://redwood.berkeley.edu/amir/vs298/roweis-saul-manifold.pdf Nonlinear Dimensionality Reduction by Locally Linear Embedding], Roweis and Saul, Science 2000.
  
* [http://connes.berkeley.edu/~amir/vs298/carlsson-ijcv08.pdf On the Local Behavior of Spaces of Natural Images], Carlsson et al., Int J Comput Vis (2008) 76: 1–12.
+
* [http://redwood.berkeley.edu/amir/vs298/carlsson-ijcv08.pdf On the Local Behavior of Spaces of Natural Images], Carlsson et al., Int J Comput Vis (2008) 76: 1–12.
  
 
Additional reading:
 
Additional reading:
  
* [http://connes.berkeley.edu/~amir/vs298/webster-face-adaptation.pdf Adaptation to natural facial categories], Michael A. Webster, Daniel Kaping, Yoko Mizokami & Paul Duhamel, Nature, 2004.
+
* [http://redwood.berkeley.edu/amir/vs298/webster-face-adaptation.pdf Adaptation to natural facial categories], Michael A. Webster, Daniel Kaping, Yoko Mizokami & Paul Duhamel, Nature, 2004.
  
* [http://connes.berkeley.edu/~amir/vs298/leopold.pdf Prototype-referenced shape encoding revealed by high-level aftereffects], David A. Leopold, Alice J. O’Toole, Thomas Vetter and Volker Blanz, Nature, 2001.
+
* [http://redwood.berkeley.edu/amir/vs298/leopold.pdf Prototype-referenced shape encoding revealed by high-level aftereffects], David A. Leopold, Alice J. O’Toole, Thomas Vetter and Volker Blanz, Nature, 2001.
  
 
==== 21 Oct ====
 
==== 21 Oct ====
  
* Handout on [http://connes.berkeley.edu/~amir/vs298/attractor-networks.pdf Attractor neural networks]
+
* [http://redwood.berkeley.edu/amir/vs298/attractor-networks.pdf Handout] on attractor neural networks
* [http://connes.berkeley.edu/~amir/vs298/hopfield82.pdf original Hopfield (1982) paper]
+
* [http://redwood.berkeley.edu/amir/vs298/hopfield82.pdf original Hopfield (1982) paper]
 
* HKP Chapters 2 and 3
 
* HKP Chapters 2 and 3
  
 
==== 23 Oct ====
 
==== 23 Oct ====
  
* [http://connes.berkeley.edu/~amir/vs298/hopfield84.pdf Hopfield (1984) paper]
+
* [http://redwood.berkeley.edu/amir/vs298/hopfield84.pdf Hopfield (1984) paper]
* [http://connes.berkeley.edu/~amir/vs298/zhang96.pdf Kechen Zhang paper on bump circuits]
+
* [http://redwood.berkeley.edu/amir/vs298/zhang96.pdf Kechen Zhang paper on bump circuits]
* [http://connes.berkeley.edu/~amir/vs298/olshausen-etal93.pdf Olshausen, Anderson & Van Essen, dynamic routing circuit model]
+
* [http://redwood.berkeley.edu/amir/vs298/olshausen-etal93.pdf Olshausen, Anderson & Van Essen, dynamic routing circuit model]
 +
 
 +
==== 30 Oct ====
 +
 
 +
* [http://redwood.berkeley.edu/amir/vs298/probability.pdf A probability primer]
 +
* [http://redwood.berkeley.edu/amir/vs298/bayes-prob.pdf Bayesian probability theory and generative models]
 +
 
 +
==== 4 Nov ====
 +
 
 +
* [http://redwood.berkeley.edu/amir/vs298/mog.pdf Mixture of Gaussians model ]
 +
* HKP Chapter 7, section 7.1
 +
 
 +
==== 6 Nov ====
 +
 
 +
Some suggested readings for Jon Shlens' talk.
 +
 
 +
===== Reviews=====
 +
* S.H. Nirenberg and J.D. Victor, [http://dx.doi.org/10.1016/j.conb.2007.07.002 Analyzing the activity of large populations of neurons: how tractable is the problem?], Curr Opin Neurobiol 17 (4) (2007), pp. 397--400.
 +
 
 +
* Shlens J, Rieke F, Chichilnisky E. [http://dx.doi.org/10.1016/j.conb.2008.09.010 Synchronized firing in the retina]. Curr Opin Neurobiol. 2008 Oct 27.
 +
 
 +
=====Theory=====
 +
* S. Amari (2001) [http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=930911&isnumber=20133 Information geometry on hierarchy of probability distributions]. IEEE Trans Inform Theory 47:1701-1711
 +
 
 +
* E. Schneidman, S. Still, M.J. Berry and W. Bialek, [http://prola.aps.org/pdf/PRL/v91/i23/e238701 Network information and connected correlations], Phys Rev Lett 91 (2003) 238701.
 +
 
 +
=====Experiments=====
 +
* E. Schneidman, M.J. Berry, R. Segev and W. Bialek,[http://www.nature.com/nature/journal/v440/n7087/full/nature04701.html Weak pairwise correlations imply strongly correlated network states in a neural population], Nature 4400 (7087) (2006), pp. 1007-1012.
 +
 
 +
* J. Shlens, G.D. Field, J.L. Gauthier, M.I. Grivich, D. Petrusca, A. Sher, A.M. Litke and E.J. Chichilnisky, [http://www.jneurosci.org/cgi/content/abstract/26/32/8254 The structure of multi-neuron firing patterns in primate retina], J Neurosci 260 (32) (2006), pp. 8254-8266.
 +
 
 +
* Tang A, Jackson D, Hobbs J, Chen W, Smith JL, Patel H, Prieto A, Petrusca D, Grivich MI, Sher A, Hottowy P, Dabrowski W, Litke AM, Beggs JM. [http://www.jneurosci.org/cgi/content/abstract/28/2/505 A maximum entropy model applied to spatial and temporal correlations from cortical networks in vitro]. J Neurosci. 2008 Jan 9;28(2):505-18.
 +
 
 +
==== 18 Nov ====
 +
 
 +
* [http://redwood.berkeley.edu/amir/vs298/info-theory.pdf Information theory primer]
 +
* [http://redwood.berkeley.edu/amir/vs298/handout-sparse-08.pdf Sparse coding and ICA handout]
 +
* Bell and Sejnowski, [http://redwood.berkeley.edu/amir/vs298/tony-ica.pdf An Information-Maximization Approach to Blind Separation and Blind Deconvolution], Neural Comp, 1995.
 +
* Hyvarinen, Hoyer, Inki, [http://redwood.berkeley.edu/amir/vs298/TICA.pdf Topographic Independent Component Analysis], Neural Comp, 2001.
 +
 
 +
==== 20 Nov ====
 +
 
 +
* Robbie Jacobs' [http://www.bcs.rochester.edu/people/robbie/jacobslab/cheat_sheet/sensoryIntegration.pdf notes on Kalman filter]
 +
* Greg Welch's [http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html  tutorial on Kalman filter]
 +
* [http://vision.ucla.edu/~doretto/research.html Dynamic texture models]
 +
* Kevin Murphy's [https://redwood.berkeley.edu/amir/vs298/murphy-hmm.pdf  HMM tutorial]
 +
 
 +
==== 25 Nov ====
 +
 
 +
* Chris Eliasmith, Charlie Anderson, [http://books.google.com/books?id=J6jz9s4kbfIC Neural Engineering:  Computation, Representation, and Dynamics in Neurobiological Systems], MIT Press, 2004.
 +
 
 +
Chapter 4 will be emailed to the class.
 +
 
 +
* Softky and Koch, [http://redwood.berkeley.edu/amir/vs298/softky-koch-jn93.pdf The Highly Irregular Firing of Cortical Cells Is Inconsistent with Temporal Integration of Random EPSPs], J Neuroscience, January 1993, 13(1):334-350.
 +
* Mainen and Sejnowski, [http://redwood.berkeley.edu/amir/vs298/mainen-sejnowski.pdf Reliability of Spike Timing in Neocortical Neurons], Science, Vol 268, 6 June 1995.
 +
* Shadlen and Newsome, [http://redwood.berkeley.edu/amir/vs298/shadlen-newsome1.pdf Noise, neural codes and cortical organization], Curr Opin in Neur, 1994, 4:569-579.
 +
* Shadlen and Newsom, [http://redwood.berkeley.edu/amir/vs298/shadlen-newsome1.pdf Is there a signal in the noise?], Current Opin in Neur, 1995, 5:248-250.
 +
* Softky, [http://redwood.berkeley.edu/amir/vs298/softky-commentary.pdf Simple codes versus efficient codes], Current Opin in Neuro, 1995, 5:239-247.
 +
* Izhikevich, [http://redwood.berkeley.edu/amir/vs298/izhikevich-nn03.pdf Simple model of spiking neurons], IEEE Trans Neur Networks, 14(6):2003.
 +
* Izhikevich, [http://redwood.berkeley.edu/amir/vs298/izhikevich-which-nn04.pdf Which Model to Use for Cortical Spiking Neurons?], IEEE Trans Neur Networks, 15(5):2004.
 +
 
 +
==== 4 Dec ====
 +
 
 +
* A.J. Bell, [http://redwood.berkeley.edu/amir/vs298/bell-cross-level.pdf Towards a Cross-Level Theory of Neural Learning].

Latest revision as of 07:13, 11 December 2008

2 Sep

Optional:

04 Sep

Optional reading for more background:

16 Sep

  • Handout on supervised learning in single-stage feedforward networks

18 Sep

  • 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

23 Sep

25 Sep

  • HKP Chapter 9

Optional:

30 Sep

2 Oct

Optional readings that covers material in lecture in greater depth:

7 Oct

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 Compressive Sensive Resources at Rice. It has an enormous number of recent papers related to compressed sensing and sparse coding.

9 Oct

Here are a list of references for David Zipser's talk: pdf. David also suggested the following chapter in an upcoming book by Thomas J. Anastasio: pdf (waiting for approval to post)

14 Oct

Here are some additional links to papers mentioned in lecture. Optional reading:

- Gary Blasdel, Differential Imaging of Ocular Dominance and Orientation Selectivity in Monkey Striate Cortex, J Neurosci, 1992. Another source of many of nice images are in the galleries on Amiram Grinvald's site: [1]

- From Clay Reid's lab, Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [2].

16 Oct

Additional reading:

21 Oct

23 Oct

30 Oct

4 Nov

6 Nov

Some suggested readings for Jon Shlens' talk.

Reviews
Theory
Experiments

18 Nov

20 Nov

25 Nov

Chapter 4 will be emailed to the class.

4 Dec