Abstract: Methods and systems for compressing a matrix are described. The matrix, having a plurality of rows formed by a respective plurality of vectors, is partitioned into a plurality of submatrices, each submatrix containing sub-vectors from a respective group of one or more contiguous columns of the matrix. For each given submatrix, the sub-vectors are clustered into a plurality of clusters. For each given cluster, a centroid and a variance are computed and stored, based on the sub-vectors belonging to the given cluster. A mapping relating each vector to a respective cluster in each submatrix is stored. The stored centroids, stored variances and stored mapping form a set of compressed data for reconstruction of the matrix.

Abstract: Methods and systems for compressing a matrix are described. The matrix, having a plurality of rows formed by a respective plurality of vectors, is partitioned into a plurality of submatrices, each submatrix containing sub-vectors from a respective group of one or more contiguous columns of the matrix. For each given submatrix, the sub-vectors are clustered into a plurality of clusters. For each given cluster, a centroid and a variance are computed and stored, based on the sub-vectors belonging to the given cluster. A mapping relating each vector to a respective cluster in each submatrix is stored. The stored centroids, stored variances and stored mapping form a set of compressed data for reconstruction of the matrix.