897 citations · 2.2k across the 55 of their papers we have counts for
Showing 2015 · stat.MLShow all
2 papers · 2 filters
stat.ML2015★ 9 cited
Sparse Probit Linear Mixed Model
Stephan Mandt, Florian Wenzel, Shinichi Nakajima +3
Linear Mixed Models (LMMs) are important tools in statistical genetics. When used for feature selection, they allow to find a sparse set of genetic traits that best predict a conti…
stat.ML2015★ 1 cited
Framework for Multi-task Multiple Kernel Learning and Applications in Genome Analysis
Christian Widmer, Marius Kloft, Vipin T Sreedharan +1
We present a general regularization-based framework for Multi-task learning (MTL), in which the similarity between tasks can be learned or refined using -norm Multiple Kern…