estimating maternal mortality level is constantly challenging researchers and planners both in rich and poor countries. in developing countries, particularly in burkina faso where the registration system is not working properly, censuses and surveys are the main providers of maternal mortality estimates. however, censuses provide more reliable data about maternal mortality especially at sub-nat...

Propagating input uncertainty through non-linear Gaussian process (GP) mappings is intractable. This hinders the task of training GPs using uncertain and partially observed inputs. In this paper we refer to this task as “semi-described learning”. We then introduce a GP framework that solves both, the semi-described and the semi-supervised learning problems (where missing values occur in the out...

Let us consider a case where all of the elements in some continuous slices are missing in tensor data. In this case, the nuclear-norm and total variation regularization methods usually fail to recover the missing elements. The key problem is capturing some delay/shift-invariant structure. In this study, we consider a low-rank model in an embedded space of a tensor. For this purpose, we extend a...

Automatic speech recognition (ASR) performance falls dramatically with the level of mismatch between training and test data. The human ability to recognise speech when a large proportion of frequencies are dominated by noise has inspired the “missing data” and “multi-band” approaches to noise robust ASR. “Missing data” ASR identifies low SNR spectral data in each data frame and then ignores it....

The properties of hierarchical nonlinear factor analysis (HNFA) recently introduced by Valpola and others [3] are studied by reconstructing values. The variational Bayesian learning algorithm for HNFA has linear computational complexity and is able to infer the structure of the model in addition to estimating the parameters. To compare HNFA with other methods, we continued the experiments with ...

Context and activity recognition in complex scenarios is prone to data loss due to disconnections, sensor failure, transmission problems, etc. This generally implies significant changes in the recognition performance. In the case of classifier fusion architecture faulty sensors can be removed from the recognition chain to overcome this issue. Alternatively, we can try to compensate or impute da...

In visual processing the ability to deal with missing and noisy information is crucial. Occlusions and unreliable feature detectors often lead to situations where little or no direct information about features is available. However the available information is usually sufficient to highly constrain the outputs. We discuss Bayesian techniques for extracting class probabilities given partial data...

congenitally missing of maxillary lateral incisors is one of the most common patterns of hypodontia. this paper presents a nine year old boy with congenital missing of lateral incisors. familial history showed that, his mother, aunts, uncle and grandmother have also congenital absence of lateral incisors.