DMS Colloquium: Dr. Guohui Song

Speaker: Dr. Guohui Song, Clarkson University

Title: Sparse Approximation and Distributed Optimization in Machine Learning

Abstract: Kernels and the corresponding reproducing kernel Hilbert spaces (RKHS) have already seen their successful applications in machine learning. The benefit of the kernel mapping allows us to deal with the nonlinearity through linear algorithms. On the other hand, sparse representation has been proven to be beneficial and favorable in computation. However, the norm in RKHS usually does not induce sparse representations. We will construct reproducing kernel Banach spaces (RKBS) with certain sparsity-inducing norms, such as the l1 norm. In particular, we will study the sparse approximation models in such RKBS. Moreover, we will also develop distributed algorithms for solving these optimization models.