We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
In this paper we analyze the bi-conjugate gradient algorithm in finite precision arithmetic, and suggest reasons for its often observed robustness. By using a tridiagonal structure...
In this paper, we propose two-channel filter-bank designs for signals defined on arbitrary graphs. These filter-banks are local, invertible and critically sampled. Depending on th...
Abstract. We consider dynamic evaluation of algebraic functions (matrix multiplication, determinant, convolution, Fourier transform, etc.) in the model of Reif and Tate; i.e., if f...
Gudmund Skovbjerg Frandsen, Johan P. Hansen, Peter...
One of the strongest techniques available for showing lower bounds on quantum communication complexity is the logarithm of the approximation rank of the communication matrix— th...