To what extent is learnability impeded when information is missing in learning instances? We present relevant known results and concrete open problems, in the context of a natural extension of the PAC learning model that accounts for arbitrarily missing information.

In contrast to the theories of relativity, quantum mechanics is not yet based on a generally accepted conceptual foundation . It is proposed here that the missing principle may be identified through the observation that all knowledge in physics has to be expressed in propositions and that therefore the most elementary system represents the truth value of one proposition , i.e., it carries just ...

In this paper we compute the expected Fisher information and the asymptotic variance-covariance matrix of the ML estimates based on progressively Type-II censored sample from Weibull distribution by direct calculation as well as the missing information principle. These values are then used to determine the optimal progressive censoring plans. Three optimality criteria are considered and some se...

The Weibull distribution is a very popular distribution for modeling lifetime data. Left truncation and right censoring are often observed in lifetime data. Here, the EM algorithm is applied to estimate the model parameters of the Weibull distribution fitted to data containing left truncation and right censoring. The maximization part of the EM algorithm is carried out using the EM gradient alg...