OPTIMIZATION (FRANCESCO RINALDI)
Corso
A Padova
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Descrizione
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Tipologia
Corso
-
Luogo
Padova
- Written exam
- Homeworks
- Project (Optional)
1) Homeworks will periodically be assigned based on reading and lecture and will be due at given deadlines.
2) Written exam consists of 5 open questions.
3) Project (optional) can be requested to better analyze specific topics.
Written exams represents 85% of grade.
Homeworks represent 15% of grade.
Project gives an increase (1 up to 3 points) of the grade.
Sedi e date
Luogo
Inizio del corso
Inizio del corso
Opinioni
Materie
- C
- C#
- C++
Programma
(a) LP models for Data science;
(b) Duality;
(c) Simplex method;
(d) Interior point methods;
2. Convex sets and convex functions
(a) Convexity: basic notions;
(c) Convex functions: Basic notions and properties (gradients, Hessians..);
3. Unconstrained convex optimization
(a) Models in data science;
(b) Characterizations of optimal sets;
(c) Gradient-type methods;
(d) Block coordinate gradient methods;
(e) Stochastic optimization methods;
4. Constrained convex optimization
(a) Models in data science;
(b) Characterizations of optimal sets;
(c) Polyhedral approximation methods;
(d) Gradient projection methods;
5. Large scale network optimization
(a) Network models in data science;
(b) Methods for distributed optimization.
Hai bisogno di un coach per la formazione?
Ti aiuterà a confrontare vari corsi e trovare l'offerta formativa più conveniente.
OPTIMIZATION (FRANCESCO RINALDI)