Speaker：Dr. Huai'an Diao

                       Northeast Normal University

Title:  Sketching for Kronecker Product Regression and P-splines

       Time：3 July 2019, 16:00

Location：实验楼108

Abstract:  TensorSketch is an oblivious linear sketch introduced in (Pagh, 2013) and later used in (Pham and Pagh, 2013) in the context of SVMs for polynomial kernels. It was shown in (Avron et al., 2014) that TensorSketch provides a subspace embedding, and therefore can be used for canonical correlation analysis, low rank approximation, and principal component regression for the polynomial kernel. We take TensorSketch outside of the context of polynomials kernels, and show its utility in applications in which the underlying design matrix is a Kronecker product of smaller matrices. This allows us to solve Kronecker product regression and non-negative Kronecker product regression, as well as regularized spline regression. Our main technical result is then in extending TensorSketch to other norms. That is, TensorSketch only provides input sparsity time for Kronecker product regression with respect to the 2-norm. We show how to solve Kronecker product regression with respect to the 1-norm in time sublinear in the time required for computing the Kronecker product, as well as for more general p-norms.

Speaker  Introduction：刁怀安，博士毕业于香港城市大学，东北师范大学数学与统计学院副教授，研究方向数值代数与反散射问题，在Mathematics of Computation, BIT, Numerical Linear Algebra with Applications等期刊发表科研论文三十余篇；出版学术专著一本；现为吉林省工业与应用数学学会第四届理事会理事；曾多次赴普渡大学、麦克马斯特大学、汉堡工业大学、日本国立信息研究所、香港科技大学、香港浸会大学等高校进行合作研究与学术访问。

        联系人：白正简教授