There was a large entry of 32 teams from 12 countries.
To tackle the noise influence of the dataset, only k largest entries of each representation are kept in the subspace clustering.
Utilizing this knowledge, the estimated set of assigned signatures (widehat {mathcal {T}}_{mathrm {A}}) is dictated by the K largest entries of signal recovery (widehat {mathbf {x}}).
In these figures, dark pixels correspond to small values of the log-likelihood or path mismatch penalty and bright pixels correspond to larger entries of the corresponding matrices.
For two vectors (mathbf{x},mathbf{y}in[alpha,beta]^{l}), let (x_{[i]},y_{[i]}) denote the ith largest entries of x and y, respectively.
And then, Υ l is identified as the set of coordinates corresponding to the k largest entries of h l and Λ is expanded as Λ=Λ∪Υ l.
These and other transform coding techniques essentially involve computing the expansion coefficients α describing the signal in some basis Ψ, keeping only the K-largest entries of α, and setting the rest to zero.
We see that, decreasing the value of L, on the one hand, will decrease the value of 1 ( N - L + 1 ) 2 ; on the other hand, it will also decrease the eigenvalues σ ̃ i 2, resulting in larger entries of d ̃ σ In fact, from (11) and (14), we see that, the effect of L resembles the smoothing technique in array signal processing.
Taking P ^ s s to be the solution of Eq. 5 and using the fact that the deterministic steady state solution is unique, we observe that P ^ s s (X0) is among the largest entries of P ^ s s.
The subproblem (11a) can be solved by updating L with an arbitrary initialization using [ 14] (12) L t ⟵ T λ P Ω X − S t − 1 + P Ω ⊥ L. The solution of subproblem (11b) is (13) S t = P Θ P Ω X − L t, where Θ is the nonzero subset of the first k largest entries of | 𝒫 Ω (X − L t )|.
