Te-Won Lee: Refereed Publications

Guideline through my paper collection: An ICA review paper is Lee00cm, for ICA algorithms see Lee99nc and check out the matlab code. For multichannel blind deconvolution see Lee97nips, Lee97icnn and Lee98icassp. Overcomplete ICA is in Lee99spl. A paper on nonlinear ICA is Lee97nnsp. ICA on EEG recordings are in Jung98nips and Jung98p. Analysis of fMRI data is in McKeown98pnas.A good review paper on using ICA for biomedical signal processing is in Jung01IEEE. The most recent work I have been doing is in Lee99nips and Lee99ica. The paper Lee00pami is a detailed version of Lee99nips and Lee99ica. Work on color and spectral data is in Wachtler00josa. Recently work on medical informatics in collaboration with the Medical School at UCSD is in Goldbaum01IVOS. A complete list of my papers is available as PS or PDF file (ps, pdf).

Check out the ICA Book!

Independent Component Analysis: Theory and Applications,
Te-Won Lee, Kluwer Academic Publishers, September 1998
ISBN: 0 7923 8261 7, table of contents
Preface by Terry Sejnowski
Order here.
Order through Amazon.com (this is faster)

Journals

[Goldbaum01IVOS] M.H. Goldbaum, P.A. Sample, J. M. Williams K.L. Chan, T.W. Lee, D. Najafi, T.J. Sejnowski, R.N. Weinreb.
Comparing Machine Classifiers for Diagnosing Glaucoma from Standard Automated Perimetry, Investigative Ophthalmology and Vision Science (IOVS) 2001

[Lee02TIP] T-W. Lee and M.S. Lewicki
Unsupervised classification, segmentation and de-noising of images using ICA mixture models, IEEE Transactions on Image Processing, January 2002.

[Jung01IEEE] Jung, T-P, Makeig, s, McKeown, M. J., Bell, A. J., Lee, T-W, Sejnowski, T. J., Imaging brain dynamics using Independent Component Analysis (.pdf, 640k), Proceedings of the IEEE, 89(7):1107-22, 2001.

[Wachtler01josa] T. Wachtler, T.-W. Lee and T.J. Sejnowski The Chromatic Structure of Natural Scenes, Journal of the Optical Society of America, A, Vol 18 (1), 65-77, Jan. 2001.

[Lee00pami] T-W. Lee, M.S. Lewicki and T.J. Sejnowski.
ICA Mixture Models for Unsupervised Classification of Non-Gaussian Sources and Automatic Context Switching in Blind Signal Separation, IEEE Transactions on Pattern Recognition and Machine Intelligence 22(10), 1-12, Oct. 2000. PDF

[Bae00el] U.-M. Bae, T.-W. Lee and S.-Y. Lee. Blind signal separation in teleconferencing using the ICA mixture model, Electronic Letters, Vol. 37(7), 680-682, 2000.

[Jung00p] T.P Jung, S. Makeig, C. Humphries, T-W. Lee, M. McKeown, V. Iragui, T.J. Sejnowski.
Removing Electroencephalographic Artifcats by Blind Source Separation , Psychophysiology, 37:167-78, March 2000.

[Lee00cm] T-W. Lee, M. Girolami, A.J. Bell and T.J. Sejnowski.
A Unifying Information-theoretic Framework for Independent Component Analysis, computers & mathematics with applications, Vol 31 (11), 1-21, March 2000. PDF

[Park99el] H.-M. Park, H.-Y. Jung, T.-W. Lee and S.-Y. Lee. On Subband-Based Blind Signal Separation for Noisy Speech Recognition, Electronic Letters, Vol. 35(23), 2011-2012, 1999.

[Lee99spl] T-W. Lee, M.S. Lewicki, M. Girolami and T.J. Sejnowski.
Blind Source Separation of More Sources Than Mixtures Using Overcomplete Representations, IEEE Signal Processing Letters Vol. 4, No. 4., April 1999, PDF

[Lee99nc] T-W. Lee, M. Girolami and T.J. Sejnowski.
Independent Component Analysis using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources, Neural Computation, 1999, Vol.11(2): 417-441,PDF.
(Matlab-code)

[McKeown98pnas] M. McKeown, T.P. Jung, S. Makeig, G. Brown, S. Kindermann, T-W. Lee, T.J. Sejnowski.
Spatially Independent Activity Patterns in Functional Magnetic Resonance Imaging Data During the Stroop Color-naming Task, Proceedings of the National Academy of Sciences, 1998, 95:803-10. PDF

[Motamed98tcs] M. Motamed, A. Zakhor, S. Sanders, T-W. Lee.
Spectral Characteristics of the Double Loop Sigma-Delta Modulator, IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, Jan. 1998, vol.45, (no.1):144-7

Bookchapters

[Lee01nips] T-W. Lee, T. Wachtler and T.J. Sejnowski.
Color Opponency Constitutes A Sparse Representation For the Chromatic Structure of Natural Scenes , Advances in Neural Information Processing Systems 13, 2001, MIT Press, Cambridge MA.

[Lee99nips] T-W. Lee, M.S. Lewicki and T.J. Sejnowski.
Unsupervised Classification with Non-Gaussian Mixture Models using ICA , Advances in Neural Information Processing Systems 11, 1999, MIT Press, Cambridge MA.

[Jung98nips] T.P Jung, C. Humphries, T-W. Lee, S. Makeig, M. McKeown, V. Iragui, T.J. Sejnowski. ICA Removes Artifacts from Electroencephalographic Recordings, Advances in Neural Information Processing Systems 10, 1998, MIT Press, Cambridge MA, pp 894-900.

[Lee97nips] T-W. Lee, A.J. Bell and R. Lambert. Blind separation of delayed and convolved sources, Advances in Neural Information Processing Systems 9, 1997, MIT Press, Cambridge MA, pp 758-764,

Conference Proceedings

[LeeJH00ica] J-H. Lee, H-J. Jung, T-W. Lee and S-Y. Lee. " Speech Coding and Noise Reduction Uusing ICA-based Speech Features" International Workshop on Independent Component Analysis (ICA'00), Helsinki, pages 417-422, June 2000.

[Jung00ica] T.-P. Jung, S. Makeig, T.-W. Lee, M. McKeown, G. Brown, A. J. Bell, T. J. Sejnowski. Independent Component Analysis of Biomedical Signals, International Workshop on Independent Component Analysis (ICA'00), Helsinki, pages 633-644, June 2000.

[Lee00ica] T.-W. Lee, M. S. Lewicki The Generalized Gaussian Mixture Model Using ICA, International Workshop on Independent Component Analysis (ICA'00), Helsinki, pages 239-244, June 2000.

[Lee00icassp] J-H. Lee, H-J. Jung, T-W. Lee and S-Y. Lee. Speech Feature Extraction Using Independent Component Analysis IEEE International Conference on Acoustics, Speech and Signal Processing, III 1631-4, June 2000.

[Lee00gfkl] T.-W. Lee, M. S. Lewicki "Unsupervised classification of non-Gaussian sources", Proceedings of the 24th Gesellschaft fuer Klassifikation, Springer Verlag March 2000.

[Lee00bmcv] T.-W. Lee, T. Wachtler and T.J. Sejnowski The Spectral Independent Components of Natural Scenes, Biologically Motivated Computer Vision, Springer Verlag, May 2000.

[Lee00aip] T.-W. Lee Nonlinear Approaches to Independent Component Analysis, Proceedings of the American Institute of Physics, Oct. 1999.

[Park99iconip] H.-M. Park, H.-Y. Jung, T.-W. Lee and S.-Y. Lee "On Subband-Based Blind Source Separation for Noisy Speech Recognition", International Conference On Neural Information Processing, Vol. 1, 204-209, 1999.

[Kreutz99inc] K. Kreutz-Delgado, B.D. Rao, K. Engan, T-W. Lee and T.J. Sejnowski.
Learning Overcomplete Dictionaries: Convex/Schur-Convex (SCS) Log-Priors, Factorial Codes, and Independent/Dependent Component Analysis (I/DCA), 6th Joint Symposium on Neural Computation, Institute for Neural Computation, pages 72-78, May 1999.

[Kreutz99inc] K. Kreutz-Delgado, B.D. Rao, K. Engan, T-W. Lee and T.J. Sejnowski.
Convex/Schur-Convex (CSC) Log-Priors and Sparse Coding, 6th Joint Symposium on Neural Computation, Institute for Neural Computation, pages 65-71, May 1999.

[Lee99inc] T-W. Lee, M.S. Lewicki and T.J. Sejnowski.
ICA mixture models for image processing, 6th Joint Symposium on Neural Computation, Institute for Neural Computation, pages 79-86, May 1999.

[Lee99ica] T-W. Lee and M.S. Lewicki and T.S. Sejnowski.
ICA Mixture Models For Unsupervised Classification And Automatic Context Switching , International Workshop on Independent Component Analysis (ICA'99), Jan. 99, Aussie, pp. 209-214.

[Jung98nnsp] T.P Jung, C. Humphries, T-W. Lee, M. McKeown, V. Iragui, S. Makeig, T.J. Sejnowski.
Removing Electroencephalographic Artifacts: Comparison between ICA and PCA, IEEE International Workshop on Neural Networks for Signal Processing, Sept. 98, pp. 63-72.

[Lee98icassp] T-W. Lee, A. Ziehe, R. Orglmeister and T.J. Sejnowski.
Combining time-delayed decorrelation and ICA: towards solving the cocktail party problem , Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing , May 1998, Seattle, Vol 2, pp. 1249-1252.

[Koehler97icann] B.U. Koehler, T-W. Lee andR. Orglmeister.
Improving The Performance of Infomax Using Statistical Signal Processing Techniques, Proceedings International Conference on Artificial Neural Networks, Nov. 97, Lausanne, pp. 535-540.

[Makeig97pr] S. Makeig, T.P. Jung, T-W. Lee, T.J. Sejnowski.
Independent component analysis of steady-state responses, 37th Meeting of the Society for Psychophysiological Research, Oct. 97, Falmouth, MA.

[Lee97nnsp] T-W. Lee, B.U. Koehler and R. Orglmeister.
Blind Source Separation of Nonlinear Mixing Models, Proceedings of IEEE International Workshop on Neural Networks for Signal Processing, Sept. 97, Florida, pp 406-415.

[Lee97icnn] T-W. Lee, A.J. Bell and R. Orglmeister.
Blind Source Separation of Real World Signals, Proceedings of IEEE International Conference Neural Networks, June 97, Houston, pp 2129-2135.

[Lee97inc] T-W. Lee and T.J. Sejnowski.
Independent Component Analysis for Sub-Gaussian and Super-Gaussian Mixtures, 4th Joint Symposium on Neural Computation, Institute for Neural Computation, 1997, vol.7, pp 132-139,

[Lee97icassp] T-W. Lee and R. Orglmeister.
A Contextual Blind separation of delayed and convolved sources, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, April 97, Munich, pp 1199-1203.

[Motamed96iscas] M. Motamed, A. Zakhor, S. Sanders, T-W. Lee
Spectral Characteristics of the Double Loop Sigma-Delta Modulator, Proceedings of IEEE International Symposium on Circuits and Systems, May 96, Atlanta, vol.1,pp 457-460.

Submitted Papers

[Kreutz99sub] K. Kreutz-Delgado, B.D. Rao, K. Engan, T-W. Lee and T.J. Sejnowski.
Supergaussian Priors - Sufficient for Sparse Coding?, submitted for publication

[Lee99sub1] T-W. Lee, T. Wachtler and T.J. Sejnowski.
The Independent Components Of Color Images, submitted for publication

[Lee99sub2] T-W. Lee, M.S. Lewicki and T.J. Sejnowski.
Unsupervised classification, segmentation and de-noising of images using ICA mixture models, submitted for publication