Te-Won Lee
Affiliations: | Electrical Engineering (Communication Theory and Systems) | University of California, San Diego, La Jolla, CA |
Area:
Electronics and Electrical Engineering, Computer ScienceGoogle:
"Te-Won Lee"
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Publications
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| Hao J, Lee TW, Sejnowski TJ. (2010) Speech Enhancement Using Gaussian Scale Mixture Models. Ieee Transactions On Audio, Speech, and Language Processing. 18: 1127-1136 |
| Hao J, Lee I, Lee TW, et al. (2010) Independent vector analysis for source separation using a mixture of gaussians prior. Neural Computation. 22: 1646-73 |
| Hao J, Attias H, Nagarajan S, et al. (2009) Speech Enhancement, Gain, and Noise Spectrum Adaptation Using Approximate Bayesian Estimation. Ieee Transactions On Audio, Speech, and Language Processing. 17: 24-37 |
| Bowd C, Hao J, Tavares IM, et al. (2008) Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyes. Investigative Ophthalmology & Visual Science. 49: 945-53 |
| Lee JH, Lee TW, Jolesz FA, et al. (2008) Independent vector analysis (IVA): multivariate approach for fMRI group study. Neuroimage. 40: 86-109 |
| Kim T, Attias HT, Lee S, et al. (2007) Blind Source Separation Exploiting Higher-Order Frequency Dependencies Ieee Transactions On Audio, Speech, and Language Processing. 15: 70-79 |
| Lee I, Kim T, Lee T. (2007) Fast fixed-point independent vector analysis algorithms for convolutive blind source separation Signal Processing. 87: 1859-1871 |
| Eltoft T, Kim T, Lee T. (2006) On the multivariate Laplace distribution Ieee Signal Processing Letters. 13: 300-303 |
| Park H, Lee T. (2006) Capturing nonlinear dependencies in natural images using ICA and mixture of Laplacian distribution Neurocomputing. 69: 1513-1528 |
| Sample PA, Boden C, Zhang Z, et al. (2005) Unsupervised machine learning with independent component analysis to identify areas of progression in glaucomatous visual fields. Investigative Ophthalmology & Visual Science. 46: 3684-92 |