Figure 3:
Visualizing the matrix, equation 3.6 for St-RKM models after training on three data sets. The first two rows show, equation 3.6, where U=U★∈St(ℓ,m) is the output of algorithm 1. These matrices are effectively close to being diagonal and especially for St-RKM-sl, as expected. In contrast, the third row shows the same matrix, equation 3.6, with U∈St(ℓ,m) sampled uniformly at random (see Table 6 for the corresponding normalized diagonalization errors).

Visualizing the matrix, equation 3.6 for St-RKM models after training on three data sets. The first two rows show, equation 3.6, where U=USt(,m) is the output of algorithm 1. These matrices are effectively close to being diagonal and especially for St-RKM-sl, as expected. In contrast, the third row shows the same matrix, equation 3.6, with USt(,m) sampled uniformly at random (see Table 6 for the corresponding normalized diagonalization errors).

Close Modal

or Create an Account

Close Modal
Close Modal