Sentence examples for learning matrix from inspiring English sources
In a supervised training, the 3D learning matrix increases its size to contain the vector-images of the (15+3)D 5BLC/BLC6 input vectors, this matrix will be later used for prediction purpose.
This is a supervised training, where each input vector is formed by the union of the 15+3 components in an 18D vector, the learning matrix W i,j,k) becomes now of dimension (50×50×18), and the calculation proceeds like the non-supervised training.
Based on lifting technique and Youla-parametrization, the 2-DOF controller design, i.e., the design of ILC and IFT, is formulated into one constrained optimization problem where an optimal combination of the learning matrix and feedback controller is found in each iteration with guaranteed stability.
In an unsupervised training, the KNN allows simultaneous memorization of all input 15D 5BLC vectors in a 3D learning matrix.
The unsupervised learning matrix with 1975 94, which is not in Table 7, gives a 5BLC localization error of 0.22, lower than that of supervised learning, as expected.
We decided instead to use a 162×162 map, allowing 3.4 neurons per learning vector and we needed numE = 10000 epochs to reach convergence in the learning matrix.
Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning.
550 sentences (5 sentences each person) were selected randomly as the training data for learning projection matrix in different subspaces and 32 dimension sparse tensor representation are extracted.
Recently, various researchers have considered manifold learning in matrix factorization.
For instance, Cai et al. [ 22] showed that adding manifold learning in matrix factorization will improve clustering performance substantially.
170 sentences (5 sentences each person) were selected randomly as the training data for learning projection matrices in different subspaces.
