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Max Little

Max Little leads a group of researchers studying algorithms for statistical machine learning in signal processing. His background is in applied mathematics and computer science. The unifying theme of his research is machine learning in statistical signal processing. Most of his applied work is in biomedical engineering, in particular algorithms for digital health using wearable devices and smartphones.

Advances in Machine Learning for DSP

Available in 13 days, 2 hours and 16 minutes

Machine learning has advanced to the point where it is now feasible to incorporate it directly into DSP applications. The major advantage is in the ability for DSP algorithms to "learn" to perform well. In this talk we will discuss how methods such as nonlinear and non-Gaussian inference and Bayesian nonparametrics can be exploited to develop novel DSP algorithms with a much higher level of specificity and efficiency than classical LTI methods.

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