Gradient Descent Insights
David explores using gradient descent for spectral methods in deep learning, highlighting the advantages of automatic decomposition in PCA compared to traditional methods like training a Vae. The optimization challenges and messy convergence reveal the complexities of implementing this approach effectively.In this clip
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The Gradient
David Pfau: Manifold Factorization and AI for Science
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