Derives ODE limits of Adam-DA showing that first- and second-order momentum parameters reverse their convergence roles in zero-sum games compared to minimization, validated on GAN experiments.
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AHGCDD distills large hypergraphs into informative synthetic versions via anchor-guided joint optimization and dual-level discrimination, achieving better effectiveness and efficiency than prior decoupled HGC approaches.
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Understanding Dynamics of Adam in Zero-Sum Games: An ODE Approach
Derives ODE limits of Adam-DA showing that first- and second-order momentum parameters reverse their convergence roles in zero-sum games compared to minimization, validated on GAN experiments.
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Anchor-guided Hypergraph Condensation with Dual-level Discrimination
AHGCDD distills large hypergraphs into informative synthetic versions via anchor-guided joint optimization and dual-level discrimination, achieving better effectiveness and efficiency than prior decoupled HGC approaches.