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» Generalization Error Bounds Using Unlabeled Data
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SIGIR
2006
ACM
15 years 4 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
VRCAI
2006
ACM
15 years 4 months ago
Parallel-split shadow maps for large-scale virtual environments
Shadowing effects dramatically enhance the realism of virtual environments by providing useful visual cues. Shadow mapping is an efficient algorithm for real-time shadow renderin...
Fan Zhang, Hanqiu Sun, Leilei Xu, Lee Kit Lun
INFOCOM
2011
IEEE
14 years 1 months ago
User-centric data dissemination in disruption tolerant networks
Abstract—Data dissemination is useful for many applications of Disruption Tolerant Networks (DTNs). Current data dissemination schemes are generally network-centric ignoring user...
Wei Gao, Guohong Cao
STOC
2004
ACM
145views Algorithms» more  STOC 2004»
15 years 10 months ago
Using mixture models for collaborative filtering
A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Jon M. Kleinberg, Mark Sandler
BMCBI
2007
239views more  BMCBI 2007»
14 years 10 months ago
Pre-processing Agilent microarray data
Background: Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to...
Marianna Zahurak, Giovanni Parmigiani, Wayne Yu, R...