Some example papers.
This list is not exhaustive, these are just a few examples. Students can come up with other papers that they are interested in. The choice is entirely up to the students.
T. Toyoizumi, J.-P. Pfister, K. Aihara, W. Gerstner: S
pike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model
Advances in Neural Information Processing Systems 17, MIT Press
G Chechik, A Globerson, N Tishby,Y Weiss
Information Bottleneck for Gaussian variables.
J. Machine Learning Research 6(Jan) p.165-188, 2005
Information-based objective functions for active data selection
Statistical Inference, Occam's Razor and Statistical Mechanics on The Space of Probability Distributions,
Vol.9, No.2, Feb. 1997
Occam factors and model-independent Bayesian learning of continuous distributions
. I Nemenman & W Bialek,
Phys Rev E
65, 026137 (2002)
S. Tong, D. Koller:
Support Vector Machine Active Learning with Applications to Text Classification
Journal of Machine Learning Research. Volume 2, pages 45-66. 2001
A Bordes, S Ertekin, J Weston, L Bottou,
Fast Kernel Classifiers with Online and Active Learning
Journal of Machine Learning Research
, vol. 6, pp. 1579-1619, Sep. 2005
Field theories for learning probability distributions
W Bialek, CG
Callan & SP Strong,
Phys Rev Lett
77, 4693-4697 (1996)
W Bialek, I Nemenman & N Tishby,
Complexity through nonextensivity
R. Linsker, Self-organization in a perceptual network.
Chris Watkins and Peter Dayan. Q-Learning. Machine Learning, 8:279--292, 1992.