Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Som...
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Abstract. This paper presents a design-space exploration of an applicationspecific instruction-set processor (ASIP) for the computation of various cryptographic pairings over Barre...
David Kammler, Diandian Zhang, Dominik Auras, Gerd...
In this paper we present a sublinear time (1+ )-approximation randomized algorithm to estimate the weight of the minimum spanning tree of an n-point metric space. The running time...
We present new algorithms on commodity graphics processors to perform fast computation of several common database operations. Specifically, we consider operations such as conjunct...
Naga K. Govindaraju, Brandon Lloyd, Wei Wang 0010,...