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Category Archives: machine learning
Linear MIxed Models
Linear Mixed Models (LMM) are becoming quite popular in population genetics. I have seen it used primarily in two settings: 1) in Visscher’s work to estimate the fraction of phenotypic variance explained by all the common SNPs; 2) in association studies … Continue reading
Posted in biology, machine learning
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Determinantal Point Process.
Review of 3 papers from Kulesza and Taskar on DPP. Determinantal Point Process: , where Y is a discrete set of points, and K is a kernel on Y. The benefit of DPP is that its partition function can be computed … Continue reading