8 citations · 8 across the 3 of their papers we have counts for
3 papers
stat.ML2014★ 8 cited
Multiple Output Regression with Latent Noise
Jussi Gillberg, Pekka Marttinen, Matti Pirinen +7
In high-dimensional data, structured noise caused by observed and unobserved factors affecting multiple target variables simultaneously, imposes a serious challenge for modeling, b…
stat.ML2013
Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects
Jussi Gillberg, Pekka Marttinen, Matti Pirinen +5
We consider the prediction of weak effects in a multiple-output regression setup, when covariates are expected to explain a small amount, less than , of the variance of…
stat.ME2012
Genome-wide association studies with high-dimensional phenotypes
Pekka Marttinen, Jussi Gillberg, Aki Havulinna +2
High-dimensional phenotypes hold promise for richer findings in association studies, but testing of several phenotype traits aggravates the grand challenge of association studies,…