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Explores the Blow up Technique in Variations, emphasizing its role in establishing boundedness and verifying integral fractional properties.
Covers eigenvectors, principal components, likelihood variables, EM algorithm, Jensen's inequality, and maximizing lower bounds.
Explores latent variable models, EM algorithm, and Jensen's inequality in statistical modeling.
Explores Doob inequalities, martingales, and Holder's inequality in probability theory.
Explores convexity, Jacobians, subdifferentials, and convergence rates in optimization and function analysis.
Covers upper and lower bounds, Jensen's inequality, and amended bounds in mathematical analysis.
Covers information measures like entropy, Kullback-Leibler divergence, and data processing inequality, along with probability kernels and mutual information.
Covers advanced numerical analysis topics including deep neural networks and optimization methods.
