- Docente: Riccardo Rovatti
- Credits: 6
- SSD: ING-INF/01
- Language: Italian
- Moduli: Riccardo Rovatti (Modulo 1) Luca Benini (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
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Corso:
Second cycle degree programme (LM) in
Advanced Automotive Engineering (cod. 9239)
Also valid for Second cycle degree programme (LM) in Electronic Engineering (cod. 0934)
Course contents
The two dimensions of "Big" in Big Data.
Data dimensionality
- geometrical effect of high dimensionality and consequences
Dimensionality reduction
- multidimensional Gaussian vectors and their properties
- dimensionality reduction by Johnson-Lindenstrauss
- dimensionality reduction by SVD/PCA (relationship with Gaussian clustering)
- dimensionality reduction by sparse signal recovery/compressed sensing
- other uses of SVD/eigenstructures: the hub-authority ranking, the pagerank core idea, document collection summaries)
Interpolation
- grid-data multilinear interpolation
- grid-data piecewise-linear interpolation
- scattered-data interpolation by radial-basis functions
Streaming algorithms
- the streaming computation model
- streaming random picks and multiplication of huge matrices
- streaming estimation of features of occurences histogram
- hashing for flattening of distributions
- random computation: estimations instead of exact results
Teaching methods
Class teaching
Assessment methods
Oral examination
Office hours
See the website of Riccardo Rovatti
See the website of Luca Benini