Estimation via sampling out of highly selective join queries is well known to be problematic, most notably in online aggregation. Without goal-directed sampling strategies, samples...
— The limited number of orthogonal channels and the autonomous installations of hotspots and home wireless networks often leave neighboring 802.11 basic service sets (BSS’s) op...
Chun-cheng Chen, Eunsoo Seo, Hwangnam Kim, Haiyun ...
Abstract. A classical problem in query optimization is to find the optimal ordering of a set of possibly correlated selections. We provide an ion of this problem as a generalizati...
In this paper, we propose a novel framework for face super-resolution based on a layered predictor network. In the first layer, multiple predictors are trained online with a dynami...
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...