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Lee-Laboratory for Machine Learning and Signal Processing. |
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[left to right: Steven, Oh-Wook, Jorge, Suman, Eizaburo, Gil-Jin, Manabu, Erik, Te-Won] |
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The goals of our laboratory are to develop new learning algorithms and methods for signal processing, image processing and exploratory data analysis. The inspirations for novel algorithms come from the understanding of how the brain represents and learns sensory information. These insights can be used to develop algorithms that can be implemented to perform machine learning tasks such as automatic speech recognition, unsupervised learning and filtering of sounds and automatic classification of diseases. This framework allows us to understand how the brain processes information such as vision where the derived models provide a mathematical understanding of the early visual system. We believe that basic research in neural information processing systems can provide novel solutions for many signal and image processing problems.
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