Sentence examples for sparse differences from inspiring English sources

Our detailed panel data from three consecutive grades (six through eight) allow us to identify effects of peers based on year-to-year changes in students' peers as they progress through middle school rather than relying on sparse differences such as that between fourth and seventh grade or on transitions between primary school and middle school.

A huge mass of studies have been performed, but there is only sparse evidence of differences in continuation rates between different types of hormonal contraceptives.

Normalisation tends to give more sparse results than difference, particularly for MCs I, due to division of low values.

On the sparse grid, the finite differences are used to approximate the derivatives.

The proposed architecture can be used if the successive sample differences are sparse.

Data in range mode are sparse because of slight differences between the Time Index (TI) and UTC, as well as the motion of the spacecraft.

These factors would tend to minimize the acoustic differences between sparse and continuous imaging conditions.

Up to now preliminary data were too sparse to detect any differences of important input parameters – like screen performance and program costs – between settings.

Even though both included studies reported improvement in health provider practices after training, a generalisable conclusion of effectiveness cannot be inferred given the sparse data available and differences between training interventions and outcomes examined.

As discussed before (see Section 3.6), the sparse GLM and NRC contain three fundamental differences: the two methods optimize different objective functions, use different regularization methods, and the GLM takes into account the recent firing probability of the neuron, while NRC does not.

We believe that this discrepancy is related to the difference between sparse coding (reconstruction of an observed modulation spectrum in terms of a linear combination of exemplars), what it is that the Lasso solver does, and sparse classification (estimating the probability of the HMM state underlying the observed modulation spectrum), which is our final goal.