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A Constant Factor Approximation Algorithm for Event-Based Sampling
Event-Based Sampling Approximation Algorithm
2015/6/19
We consider a control system in which sensor data is transmitted from the plant to a receiver over a communication channel, and the receiver uses the data to estimate the state of the plant. Using a f...
Representations of max-stable processes based on single extreme events
extreme value statistics incremental representation max-stable process mixed moving maxima peaks-over-threshold weak convergence on function space
2012/11/23
This paper provides the basis for new methods of inference for max-stable processes \xi\ on general spaces that admit a certain incremental representation, which, in important cases, has a much simple...
Gene-centric gene-gene interaction: A model-based kernel machine method
Allele matching kernel association study gene-clustered SNPs genomic similarity reproducing kernel Hilbert space quantitative traits
2012/11/23
Much of the natural variation for a complex trait can be explained by variation in DNA sequence levels. As part of sequence variation, gene-gene interaction has been ubiquitously observed in nature, w...
Change point analysis of an exponential model based on Phi-divergence test-statistics: simulated critical points case
Change point Exponential model Likelihood ratio test Power-divergence test statistic
2011/8/25
Abstract: Recently Batsidis \textit{et al.} (2011) have presented a new procedure based on divergence measures for testing the hypothesis of the existence of a change point in exponential populations....
Consistency of Functional Learning Methods Based on Derivatives
Functional Data Analysis Consistency Statistical learning Derivatives SVM Smoothing splines RKHS Kernel
2011/6/15
In some real world applications, such as spectrometry, functional models
achieve better predictive performances if they work on the derivatives of order
m of their inputs rather than on the original...