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IEE/CSE 598: Lecture 2B (2026-02-12): Evolutionary and Linear Genetic Programming
In this lecture, we start by reviewing the strengths and weaknesses of the GA, CMA-ES (with adaptive restarts), and Stochastic Gradient Descent (SGD). This paints a picture of complementarity and not competition. Each algorithm fits within its own niche, and the algorithms can be used together to help compensate for weaknesses and find better ...
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