[29] Tengyu Ma - Non-convex Optimization for Machine Learning
The Thesis Review
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Navigating Non-Convex Optimization in Machine Learning
This chapter explores the intricacies of linear dynamical systems, highlighting the role of over-parameterization and initialization in machine learning models. It reflects on experiences at Google, emphasizing the significance of understanding non-convex optimization and its impact on model performance. Additionally, the chapter underscores the importance of integrating classical machine learning methods with modern deep learning techniques to equip students for complex tasks.
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