The low-rank matrix approximation problem involves finding of a rank k version of a m ? n matrix AAA, labeled AAAk, such that AAAk is as "close" as possible to the best ...
We study graph partitioning problems on graphs with edge capacities and vertex weights. The problems of b-balanced cuts and k-balanced partitions are unified into a new problem ca...
Guy Even, Joseph Naor, Satish Rao, Baruch Schieber
models require the identi cation of abstractions and approximations that are well suited to the task at hand. In this paper we analyze the problem of automatically selecting adequ...
Disciplined approximate programming lets programmers declare which parts of a program can be computed approximately and consequently at a lower energy cost. The compiler proves st...
Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug...
Abstract. We introduce a hybrid approach to magnetic resonance image segmentation using unsupervised clustering and the rules derived from approximate decision reducts. We utilize ...