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Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL
Minimax Multi-Task Learning a Generalized Loss-Compositional Paradigm MTL
2012/11/23
Since its inception, the modus operandi of multi-task learning (MTL) has been to minimize the task-wise mean of the empirical risks. We introduce a generalized loss-compositional paradigm for MTL that...
Online Multi-task Learning with Hard Constraints
Online Multi-task Learning Hard Constraints
2010/3/18
We discuss multi-task online learning when a decision
maker has to deal simultaneously with M
tasks. The tasks are related, which is modeled
by imposing that the M–tuple of actions taken by
the de...
Taking Advantage of Sparsity in Multi-Task Learning
Advantage Sparsity Multi-Task Learning
2010/3/18
We study the problem of estimating multiple linear regression equations for the purpose
of both prediction and variable selection. Following recent work on multi-task learning
Argyriou et al. [2008]...