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Title: | FAST MATRIX VECTOR MULTIPLICATION VIA INTERPOLATIVE DECOMPOSITION BUTTERFLY FACTORIZATION | Authors: | CHEN ZE | ORCID iD: | orcid.org/0000-0001-6293-9441 | Keywords: | Data-sparse matrix, Butterfly factorization, Interpolative decomposition, Matrix completion, Spherical harmonic transform, Block partitioning | Issue Date: | 30-Jul-2020 | Citation: | CHEN ZE (2020-07-30). FAST MATRIX VECTOR MULTIPLICATION VIA INTERPOLATIVE DECOMPOSITION BUTTERFLY FACTORIZATION. ScholarBank@NUS Repository. | Abstract: | In scientific computing, rapidly evaluating dense matrix-vector multiplication is one of the most important tasks. This thesis is to design and apply interpolative decomposition butterfly factorization (IDBF), a data-sparse representation of complementary low-rank matrices, to different kinds of application scenarios with a nearly optimal computational cost. We divide this thesis into two parts. Part I concentrates on the design of multidimensional IDBF together with a phase recovery technique that is crucially important in many application domains of IDBF. Part II is dedicated to developing a fast algorithm for the spherical harmonic transform via IDBF. | URI: | https://scholarbank.nus.edu.sg/handle/10635/184287 |
Appears in Collections: | Ph.D Theses (Open) |
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