In this paper, we present two techniques to analyze greedy approximation with nonsubmodular functions restricted submodularity and shifted submodularity. As an application of the ...
Ding-Zhu Du, Ronald L. Graham, Panos M. Pardalos, ...
Abstract. Since in general it is NP-hard to solve the minimum dominating set problem even approximatively, a lot of work has been dedicated to central and distributed approximation...
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...
ABSTRACT Motivated by data value locality and quality tolerance present in multimedia applications, we propose a new micro-architecture, Region-level Approximate Computation Buffer...