Seminar Computational Intelligence B (708.112)
Grundlagen der Informationsverarbeitung (708)
Lecturer: O.Univ.-Prof. Dr. Wolfgang Maass
Office hours: by appointment (via e-mail)
Location: IGI-seminar room,
Inffeldgasse 16b/I, 8010 Graz
Date: starting from
Oct. 13, 2004 every Wednesday,
2.15 - 3.45 p.m.
(extra time slot fridays at 2.15 p.m. for make-up
meetings in January)
Content of the seminar:
We will discuss theoretical methods that are needed for current
research in the areas computational
neuroscience and machine
Schedule of talks:
Nov. 3: possibly Maribel (otherwise Maribel will speek on Nov 24)
Theoretical parts of some recent paper by Rajesh Rao
If he sends me sufficiently early a preprint of his paper in the next N
IPS: Hierarchical Bayesian inference in networks of spiking neurons
(Advances in NIPS 17, 2005, to appear), then this might be best.
Otherwise the the talk will be about more theoretical parts of Bayesian
computation in recurrent neural circuits (Neural Computation,
16(1), 1-38, 2004) or Predictive
Coding in the Visual Cortex (Nature Neuroscience, 2(1), 79-87,
Nov. 24: Thuy
(if Maribel speeks on Nov. 24, then Thuy will move to Jan. 14)
Topic: Theory of simulated annealing, probably from the book http://portal.acm.org/citation.cfm?id=59580
Dec. 1: Malte
Topic: Theoritical results about Hebbian learning, STDP, and
Suitable would be for example material from ch. 11 of the book by
Gerstner and Kistler, or related papers by Gerstner et al.
Jan. 12: Stefan
Theory about interaction of excitation and inhibition in neural
circuits, e.g. from N Fourcaud-Trocmé, D Hansel, C van Vreeswijk
and N Brunel (2003), How
spike generation mechanisms determine the neuronal response to
fluctuating inputs, Journal of Neuroscience, 23, 11628-11640.
N Brunel (2000), Dynamics of sparsely connected networks of excitatory
and inhibitory spiking neurons, Journal of Computational Neuroscience,
Some basic theoretical arguments on that topics can also be found on
pp. 265 of the book by Dayan and Abbot.
Jan. 14: Michael (if
Maribel speeks on Nov. 24 then Michael will move to Feb. 2)
Proofs of convergence for Reinforcement Learning Algorithms
(e.g. from ch. 6 of the book D. P. Bertsekas and J. N. Tsitsiklis.
Neuro Dynamic Programming. Athena Scientific, Belmont, Massachusetts,
Balancing at the border of instability by L. Moreau and Eduardo
Sontag, Physical Review E 68(2003): 020901(1-4).
(There is also the opportunity to prove a related result which appears
to be even more relevant for neural systems, where negative feedback
aims at balancing some external excitation of a circuit).
Jan. 21: Joshi
Short term memory in echo state networks. GMD Report 152, German
National Research Center for Information Technology, 2001 (60 pp.)
Jan. 26: Hr Bachler (on some
paper related to feature selection) PDF