The expectation maximization algorithm enables parameter estimation in probabilistic models with incomplete data. In summary, the expectation maximization algorithm alternates between the steps of ...

Under these conditions, information maximization has extra properties not found in the linear case (Linsker ... This enables the network to separate statistically independent components in the inputs: ...

A global model is introduced as a latent variable to augment the joint distribution of clients' parameters and capture the common trends of different clients, optimization is derived based on the ...