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The Bayesian estimation of the conditional Gaussian parameter needs to define several a priori parameters. The proposed approach is free from this definition of priors. We use the Implicit estimation method for learning from observations without a prior knowledge. We illustrate the interest of such an estimation method by giving first the Bayesian Expectation A Posteriori estimator for conditional Gaussian parameters. Then, we describe the Implicit estimators for the same parameters. Moreover,doi:10.1080/18756891.2014.853926 fatcat:mhyjteh2z5az7byhbqpph2tm2a