Box-Cox Transform

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Explores the Box-Cox transform for modeling non-linear relationships between variables.

Explores the Rockafellar Theorem in optimal transport, focusing on c-cyclical monotonicity and convex functions.

Covers the properties and operations of convex functions.

Explores convex functions, affine transformations, pointwise maximum, minimization, Schur's Lemma, and relative entropy in mathematical optimization.

Covers the discussion of local extrema, concavity, convexity, and inflection points in functions.

Covers optimization techniques in machine learning, focusing on convexity and its implications for efficient problem-solving.

Covers the process of parameter estimation for spike times in neuron models.

Covers the concept of convex functions and their applications in optimization problems.

Introduces the key concepts of convexity and its applications in different fields.

Introduces convex optimization, focusing on the importance of convexity in algorithms and optimization problems.