In many real-life situations, we know the probability distribution of two random variables x1 and x2, but we have no information about the correlation between x1 and x2; what are ...
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
Cryptanalysis of ciphers usually involves massive computations. The security parameters of cryptographic algorithms are commonly chosen so that attacks are infeasible with availabl...
In the KL divergence framework, the extended language modeling approach has a critical problem estimating a query model, which is the probabilistic model that encodes user’s inf...