Unsupervised greedy learning of finite mixture models

Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI

Volumn 2, Issue , 2010, Pages 219-224

  Greggio, Nicola ^c   Bernardino, Alexandre ^a,b   Laschi, Cecilia ^a,b   Dario, Paolo ^c   Santos Victor, José ^a,b  

^a SCUOLA SUPERIORE SANT ANNA   (Italy)

^b INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^c NONE

Author keywords

Image processing; Machine learning; Self Adapting expectation maximization; Unsupervised clustering

Indexed keywords

DATA FITS; DATA SETS; EXPECTATION MAXIMIZATION; FINITE MIXTURE MODELS; GREEDY LEARNING; HIERARCHICAL SEARCH; KEY FEATURE; LEARNING PROCEDURES; MACHINE-LEARNING; MODEL SELECTION CRITERIA; NEW COMPONENTS; NUMBER OF COMPONENTS; SEARCH SPACES; SELF ADAPTING; SINGLE COMPONENTS; SYNTHETIC AND REAL DATA; TOPDOWN; TREE-LIKE STRUCTURES; UNSUPERVISED CLUSTERING;

ARTIFICIAL INTELLIGENCE; BINARY TREES; FEATURE EXTRACTION; IMAGE PROCESSING; IMAGING SYSTEMS; LEARNING SYSTEMS; MAXIMUM PRINCIPLE; MIXTURES;

OPTIMIZATION;

EID: 78751521957     PISSN: 10823409     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICTAI.2010.104     Document Type: Conference Paper

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