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ICDE
2010
IEEE
219views Database» more  ICDE 2010»
16 years 1 months ago
PIP: A Database System for Great and Small Expectations
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...
Oliver Kennedy, Christoph Koch
INFOCOM
2006
IEEE
15 years 7 months ago
Self-Learning Collision Avoidance for Wireless Networks
— 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 ...
ICDT
2005
ACM
128views Database» more  ICDT 2005»
15 years 7 months ago
The Pipelined Set Cover Problem
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...
Kamesh Munagala, Shivnath Babu, Rajeev Motwani, Je...
ICIP
2005
IEEE
16 years 3 months ago
Layered local prediction network with dynamic learning for face super-resolution
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...
Dahua Lin, Wei Liu, Xiaoou Tang
ICML
2008
IEEE
16 years 2 months ago
Empirical Bernstein stopping
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 ...
Csaba Szepesvári, Jean-Yves Audibert, Volod...