Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Online Multi-task Learning with Hard Constraints   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 decision maker needs to
satisfy certain constraints. We give natural examples of such restrictions and
then discuss a general class of tractable constraints, for which we introduce
computationally efficient ways of selecting actions, essentially by reducing to
an on-line shortest path problem. We briefly discuss "tracking" and "bandit"
versions of the problem and extend the model in various ways, including
non-additive global losses and uncountably infinite sets of tasks.

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The categories of this paper are: cond-mat
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The categories of this paper are: q-fin
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The categories of this paper are: econ
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-ex
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The categories of this paper are: dg-ga
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The categories of this paper are: astro-ph
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The categories of this paper are: q-bio
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The categories of this paper are: bayes-an
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The categories of this paper are: alg-geom
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The categories of this paper are: adap-org
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The categories of this paper are: nucl-th
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The categories of this paper are: quant-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: nlin