Abstract: An information processing method is disclosed. The method includes: obtaining initial feature information of to-be-queried information; performing feature processing on the initial feature information of the to-be-queried information, to obtain target feature information of the to-be-queried information, where the feature processing includes at least feature dimension processing used to process a data dimension of the initial feature information of the to-be-queried information to be a preset dimension; performing a first retrieval operation on m pieces of candidate information based on the target feature information of the to-be-queried information, to obtain a first retrieval result; and performing a second retrieval operation on the first retrieval result based on the initial feature information of the to-be-queried information, to obtain result information corresponding to the to-be-queried information. The method can quickly and efficiently implement information retrieval.

Abstract: Example parameter optimization methods and apparatus are described. In one example parameter optimization method, a data processing device obtains a Kronecker factor matrix that is used to indicate a higher-order information matrix of a neural network model, and segments the Kronecker factor matrix to obtain a plurality of square matrices. The obtained plurality of square matrices are submatrices of the Kronecker factor matrix, and main diagonal lines of the plurality of square matrices each are in a one-to-one correspondence with a part of a main diagonal line of the Kronecker factor matrix. Then, the data processing device adjusts a parameter of the neural network model based on the obtained plurality of square matrices.

Abstract: An information processing method is disclosed. The method includes: obtaining initial feature information of to-be-queried information; performing feature processing on the initial feature information of the to-be-queried information, to obtain target feature information of the to-be-queried information, where the feature processing includes at least feature dimension processing used to process a data dimension of the initial feature information of the to-be-queried information to be a preset dimension; performing a first retrieval operation on m pieces of candidate information based on the target feature information of the to-be-queried information, to obtain a first retrieval result; and performing a second retrieval operation on the first retrieval result based on the initial feature information of the to-be-queried information, to obtain result information corresponding to the to-be-queried information. The method can quickly and efficiently implement information retrieval.