Abstract :
The following topics are dealt with: machine learning; signal processing; learning theory; graphical and kernel methods; biomedical applications; Bayesian learning; sound, image and communication algorithms; pattern recognition and classification methods; statistical and probabilistic methods; blind source separation; compressive sensing; matrix and tensor factorisation; and latent variable analysis.
Keywords :
learning (artificial intelligence); signal processing; Bayesian learning; biomedical applications; blind source separation; communication algorithms; compressive sensing; graphical methods; image algorithms; kernel methods; latent variable analysis; learning theory; machine learning; matrix factorisation; pattern classification; pattern recognition; probabilistic methods; signal processing; sound algorithms; statistical methods; tensor factorisation; Analytical models; Clustering algorithms; Data models; Heuristic algorithms; Hidden Markov models; Noise measurement; Predictive models;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on
Conference_Location :
Southampton
DOI :
10.1109/MLSP.2013.6661894
