Textbooks:
[1] Zorich V. A. - Mathematical Analysis I
[2] Zorich V. A. - Mathematical Analysis II

[3] Boyd S., Vandenberghe L. - Convex Optimization

Exercise Sheets:
[Sheet 1]     [Sheet 2]     [Sheet 3]     [Sheet 4]

Classroom diary:
1 - 19/03 - Review of normed multilinear maps. The differential of a function between normed vector spaces. Uniqueness of the differential. Differentiability implies continuity. General properties of the differential.  Partial derivatives.   Ref. [2, Chapters 10.2, 10.3]

2 - 26/03 - Examples of differentials and the geometric meaning of the gradient. Regular curves and their arc-length. Equivalent curves. An example of curve with infinite length. Curvilinear integrals (of the first kind).   Ref. [1, Chapters 6.4.2]

3 - 09/04 - The finite increment theorem (opposed to the one-dimensional mean value theorem). Some consequences: sufficient condition for the differentiability, Lipschitz property. Directional derivatives and their relation with the differential. Higher order derivatives and how to calculate them.  Ref. [2, Chapters 10.4, 10.5.1, 10.5.2]

4 - 11/04 - Symmetry of higher order derivatives. Review of bilinear forms and the Hessian matrix. Differential of multilinear functions.  Ref. [2, Chapters 10.5.3, 10.5.4]

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5 - 16/04 - Taylor polynomial. Study of the Extrema of functions. Some examples. The fundamental lemma of the calculus of variations. Ref. [2, Chapter 10.6]

6 - 23/04 - Euler-Lagrange equation.  Newton's second law of motion as solution of a variational principle. Review on convex functions. Setting for the unconstrained convex optimization.   Ref. [2, Chapter 10.6] [3, Chapters 3, 9.1]

7 - 30/04 - The "strongly convex hypothesis". Relations between the norm of the gradient and the quality of the approximations of the minimum. Generalities on descent algorithms: "descent direction" and "ray search".  Two types of ray search: "exact" and "backtracking". Gradient descent. Ref. [3, Chapters 9.1, 9.2]

8 - 07/05 - Convergence analysis of the gradient descent.