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 ...
Many contemporary database applications require similarity-based retrieval of complex objects where the only usable knowledge of its domain is determined by a metric distance func...
Weijia Xu, Daniel P. Miranker, Rui Mao, Smriti R. ...
Much work has been done on learning various classes of "simple" monotone functions under the uniform distribution. In this paper we give the first unconditional lower bo...
We consider a regression problem where target values are given as intervals, and propose a statistical approach to it. Although it is hard to solve the optimization problem direct...
We consider the following question: given a two-argument boolean function f, represented as an N ? N binary matrix, how hard is to determine the (deterministic) communication comp...