The resulting blockNNGP enjoys Markov properties reflected on its sparse precision matrix. It is embedded as a prior within the class of latent Gaussian models, thus fast Bayesian inference is obtained using the integrated nested Laplace approximation. The performance of the blockNNGP is illustrated...
Since polarons are simply quasiparticles consisting of electrons dressed with the net effect of these electron-phonon interactions, it is important to understand this basic building block to fully understand conventional superconductivity, and possible extensions to nonconventional superconductors3. To this ...
The efficient processing of k-Nearest Neighbors (kNN) queries becomes increasingly complex with the rise in data dimensionality, often termed as the “curse of dimensionality” [23,24,25]. Traditional indexing algorithms like B-tree and R-tree are optimized for lower dimensions, but their performa...
the best results in terms of both imputation accuracy and preservation of data distribution can be obtained using kNN with small k in conjunction with ReliefF filtering; h) the very same conclusions as in point g can be reached when a real-life dataset with 15 % of MCAR data is taken int...
[22] because a k value of 3 resulted in a good trade-off between precision and computational cost. As shown in Fig. 2, in all cases the two kNN-based Table 1 Mutual Information formalism Term Symbol Shannon's entropy of X H(X) Joint entropy of X & Y H(X,Y ) Formula ...
By applying a block coordinate descent method on this reformulation, we are able to compute solutions to the approximation problem, which is illustrated on some examples. Illustration of Ω={x+iy|sin(θ)x<cos(θ)y<sin(θ)x,x<h<0,|x+iy|<r} =ΩC(0,θ)∩ΩV(h,+∞)∩ΩD(0,r)...
Alzheimer's Disease (AD) is considered one of the most diseases that much prevalent among elderly people all over the world. AD is an incurable neurodegenerative disease affecting cognitive functions and were characterized by progressive and collective f
data curation: Y.Z.; writing—original draft preparation: J.L.; writing—review and editing: Z.L. and L.H.; visualization: X.L. and Y.Y.; supervision: Y.Y.; project administration: R.P.; funding acquisition: Y.Y. All authors have read and agreed to the published version of the...
We study the information rates of noncoherent, stationary, Gaussian, and multiple-input multiple-output (MIMO) flat-fading channels that are achievable with nearest neighbor decoding and pilot-aided channel estimation. In particular, we investigate the b
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