Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Subject "Pattern recognition"
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Efficient Algorithms for Learning Restricted Boltzmann Machines
The probabilistic generative models learn useful features from unlabeled data which can be used for subsequent problem-specific tasks, such as classification, regression or information retrieval. The RBM is one such important ... -
Pattern recognition via Fuzzy set methods
The main objective of this thesis is the development of a methodology based on fuzzy set theory for several practical pattern recognition problems. Pattern recognition (PR) encompasses a range of problems from feature ...

