Sentence examples for length context from inspiring English sources

It's about reacting to what consumers respond positively to in terms of length, context, medium and beyond, while giving them the opportunity to continue generating their own content.

A fixed-length context window is used in order to ensure a fair comparison and a controlled environment (i.e., (sum _{i=1}^{M}(2d_{i}+1)) is a fixed value).

Thus, the temporal context needs to be more emphasised; however it may cause the loss of spatial context because of the fixed-length context window scenario, which has been adopted in this paper for a fair comparison among different approaches, as discussed in Section 3.2.

A recurrent neural network (RNN) [9] can learn an effective representation of history from the training data through recurrent connections between a hidden layer and an input layer as shown in Fig. 4. With a recurrent connection through s (t−1), the hidden layer or context layer s of RNNLM can capture longer word history than fixed-length context in an NNLM or an n-gram LM.

The arithmetic coder uses a fixed-length context to select a conditional distribution for the following base.

Mutation R266E reduces DNA binding by MutL (Junop et al., 2003; Robertson et al., 2006), most pronounced in full-length context.

In its full-length context, HHARI interacts with UbcH7 with a dissociation constant of 540 nM [ 42], which is a significantly higher affinity than typically displayed between E2s and E3s in the micromolar range [ 2, 3].

A secreted version of the LAT-1 ectodomain (ΔTM1-7; Figure 2B) and in-frame deletions of the GPS are completely devoid of rescuing activity in both truncated (ΔGPS/TMΔ2-7) (Langethal et al., 2009) and full-length context (ΔGPS; Figures 4E, 4F, and Table S1), whereas surface expression of ΔGPS is intact (data not shown).

The modest effect of the mutation in the full-length context suggests that the Gln51 interaction may be less crucial during later stages of Rev-RRE assembly and the energetic contributions to cooperative binding may shift to other interactions, possibly coupled to further rearrangements of the Rev subunit interfaces.

As a result, RNN can capture long context patterns instead of fixed-length contexts as in a traditional neural network (NN) LM [7].

The narrative has been updated and condensed by a trio of talented screenwriters (Tony Gilroy, Matthew Michael Carnahan and Billy Ray), but what has been lost is less length or context than depth.