Olivier Canévet
EPFL STI IEM LIDIAP
ELD 241 (Bâtiment ELD)
Station 11
CH-1015 Lausanne
Web site: Site web: https://idiap.epfl.ch/
EPFL > VPA > VPA-AVP-PGE > AVP-PGE-EDOC > EDEE-ENS
Enseignement & Phd
Cours
Fundamentals in statistical pattern recognition
1. Introduction
** Data representation
** Supervised/unsupervised models (from regression and classification to probability distribution modelling)
** Overview: Linear models, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Multi-Layered Perceptron (MLP), Support Vector Machines (SVM), k-Means, Gaussian Mixture Models (GMM) Hidden Markov Models (HMM), Ses
** Data representation
** Supervised/unsupervised models (from regression and classification to probability distribution modelling)
** Overview: Linear models, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Multi-Layered Perceptron (MLP), Support Vector Machines (SVM), k-Means, Gaussian Mixture Models (GMM) Hidden Markov Models (HMM), Ses