My notes (slides) during my PhD study in UMONS since Feb-2017, email me if you catch a mistake/typo
Refresh this page to avoid old cache in browser shows the old version of this page

Tutorial/Lecture material

On Gradient descent solving quadratic problems On Coordinate descent solving quadratic problems (under construction) Linear Algebra recap

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

Nonnegative Matrix Factorizations : heuristics, algorithms, theory

Matrix Completion

  • Algorithm

    • MC by Majorization-Minimization, by Proximal Point Algorithm / primal-dual method, by Augmented Lagrangian Method, by Douglas-Rachford spitting algorithm, by ADMM, by Iterative Reweighted Least Squares

Linear Algebra / Matrix Theory

Randomized Linear Algebra, Compressive Sensing, Random Matrix

Multilinear/Tensor Algebra and Tensor methods

  • Algebra

  • Theory

    • Why tensor : “easier” to get uniqueness of decomposition

Machine Learning

  • Machine Learning applications

    • Hyper-spectral imaging

    • Audio source separation

    • Electricity load profiling

    • Fluorescence spectroscopy

    • Gas Chromatography Mass Spectrum

    • Unsupervised Representation Learning

On software engineering

  • Version control

  • On efficient coding on experiments comparing multiple algorithms

  • On using LaTeX

  • On writing static webpage