87198 - STATISTICS AND ARCHITECTURES FOR BIG DATA PROCESSING M

Anno Accademico 2020/2021

  • Docente: Riccardo Rovatti
  • Crediti formativi: 6
  • SSD: ING-INF/01
  • Lingua di insegnamento: Inglese
  • Moduli: Riccardo Rovatti (Modulo 1) Luca Benini (Modulo 2)
  • Modalità didattica: Convenzionale - Lezioni in presenza (Modulo 1) Convenzionale - Lezioni in presenza (Modulo 2)
  • Campus: Bologna
  • Corso: Laurea Magistrale in Ingegneria elettronica (cod. 0934)

Conoscenze e abilità da conseguire

The course provides students with a basic knowledge of problems and corresponding techniques of solutions implied by the ever increasing amount and complexity of the data available for analyses and decisions, i.e., the so called Big-Data (BD). The corresponding issues are tackled by multiple points of view: from the abstract characterization of the mathematical properties of BD, to the hardware architectures needed to process them.

Contenuti

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

Metodi didattici

Class teaching

Modalità di verifica e valutazione dell'apprendimento

Oral examination

Orario di ricevimento

Consulta il sito web di Riccardo Rovatti

Consulta il sito web di Luca Benini