Young man, in mathematics you don't understand things. You just get used to them. (John von Neumann)

My notes (slides) since my PhD study (2017). Email me if you catch a mistake/typo.
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Tutorial/Lecture material

On Gradient descent solving quadratic problems [video]

Algebra

  • Tropical semiring / max-plus semiring

    • The max-plus semiring

Continuous Optimization

  • General Acceleration Strategies for optimization algorithms

    • Acceleration by extrapolation or linear combination of sequence

    • Acceleration by domain transformation : preconditioning

    • Acceleration by subset sampling : radomization approach, multi-grid approach, safe feature removal approach

    • Acceleration by hardware : parallization and distributived computing

  • Linear programming, Semidefinite programming, Polynomial Optimization

    • Linear Optimization

    • Semidefinite programming

    • Polynomial programming

      • Polynomial as linear combination of monomials

      • Square matricial representation of polynomial

      • Incomplete Basis and Newton’s Polytope

      • Geometry of the spectrahedron

Nonnegative Matrix Factorizations : heuristics, algorithms, theory

Matrix Completion

Linear Algebra / Matrix Theory

Randomized Linear Algebra, Compressive Sensing, Random Matrix

Multilinear/Tensor Algebra and Tensor methods

Multigrid

Machine Learning

  • Machine Learning applications

Signal Processing

Miscellaneous items

On software engineering

  • Version control

  • On efficient coding on experiments comparing multiple algorithms

  • On using LaTeX

  • On writing static webpage