Optimization
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Causal Fairness for Outcome Control
Neural Information Processing Systems
We next discuss two lines of related literature.
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Optimizing over trained GNNs via symmetry breaking
Neural Information Processing Systems
Although GNNs are powerful tools for these "forward" prediction tasks, few works discuss the "backward" (or inverse) problem defined on trained GNNs.
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Ordering-based Conditions for Global Convergence of Policy Gradient Methods
Neural Information Processing Systems
The conditions on the representation that imply global convergence are different between these two algorithms.
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