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Optimization tools are vital to data analysis and learning. The optimization perspective has provided valuable insights, and optimization formulations have led to practical algorithms with good theoretical properties. In turn, the rich collection of problems in learning and data analysis is providin ...

This talk presents techniques for nonstationarity detection in the context of speech and audio waveforms, with broad application to any class of time series that exhibits locally stationary behavior. Many such waveforms, in particular information-carrying natural sound signals, exhibit a degree of c ...

Optimization provides a valuable framework for thinking about, formulating, and solving many problems in machine learning. Since specialized techniques for the quadratic programming problem arising in support vector classification were developed in the 1990s, there has been more and more cross-ferti ...

The use of optimization as a framework for formulating machine learning problems has become much more widespread in recent years. In some cases, the demands of the machine learning problems go beyond the scope of traditional optimization paradigms. While existing optimization formulations and algori ...