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Multi-task additive models with shared transfer functions based on dictionary learning
[article]
2015
arXiv
pre-print
Additive models form a widely popular class of regression models which represent the relation between covariates and response variables as the sum of low-dimensional transfer functions. Besides flexibility and accuracy, a key benefit of these models is their interpretability: the transfer functions provide visual means for inspecting the models and identifying domain-specific relations between inputs and outputs. However, in large-scale problems involving the prediction of many related tasks,
arXiv:1505.04966v1
fatcat:rljvuv45lrcobcmubtf3v2cmge