Optimization in Machine Learning
The discussion delves into the intricate relationship between optimization and machine learning, highlighting how optimization techniques support various learning methods. Michael emphasizes the significance of gradient descent in many machine learning applications, while also addressing the limitations of traditional mathematical programming. He introduces the concept of sample efficient optimization, which seeks optimal solutions without prior knowledge of problem structure, reflecting a more aspirational approach to finding solutions.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Optimization School with Dr. Mike - #545
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