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• W2953494151 abstract "We introduce Invariant Risk Minimization (IRM), a learning paradigm to estimate invariant correlations across multiple training distributions. To achieve this goal, IRM learns a data representation such that the optimal classifier, on top of that data representation, matches for all training distributions. Through theory and experiments, we show how the invariances learned by IRM relate to the causal structures governing the data and enable out-of-distribution generalization." @default.
• W2953494151 created "2019-07-12" @default.
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• W2953494151 date "2019-07-05" @default.
• W2953494151 modified "2023-10-01" @default.
• W2953494151 title "Invariant Risk Minimization" @default.
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