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» Analysis and Application of Adaptive Sampling
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IPSN
2004
Springer
14 years 1 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
SIGECOM
2010
ACM
170views ECommerce» more  SIGECOM 2010»
14 years 15 days ago
Optimal online assignment with forecasts
Motivated by the allocation problem facing publishers in display advertising we formulate the online assignment with forecast problem, a version of the online allocation problem w...
Erik Vee, Sergei Vassilvitskii, Jayavel Shanmugasu...
SIP
2003
13 years 9 months ago
Polyphase Antialiasing in Enlargements
Changing resolution of images is a common operation. It is also common to use simple, i.e., small interpolation kernels satisfying some ”smoothness” qualities that are determi...
Daniel Seidner
BMCBI
2010
89views more  BMCBI 2010»
13 years 7 months ago
Spatial normalization improves the quality of genotype calling for Affymetrix SNP 6.0 arrays
Background: Microarray measurements are susceptible to a variety of experimental artifacts, some of which give rise to systematic biases that are spatially dependent in a unique w...
High-Seng Chai, Terry M. Therneau, Kent R. Bailey,...
BMCBI
2006
127views more  BMCBI 2006»
13 years 7 months ago
Improvement in the Reproducibility and Accuracy of DNA Microarray Quantification by Optimizing Hybridization Conditions
Background: DNA microarrays, which have been increasingly used to monitor mRNA transcripts at a global level, can provide detailed insight into cellular processes involved in resp...
Tao Han, Cathy D. Melvin, Leming M. Shi, William S...