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Found 5 papers, 5 papers with code
Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery Ticket
Graph Lottery Ticket (GLT), a combination of core subgraph and sparse subnetwork, has been proposed to mitigate the computational cost of deep Graph Neural Networks (GNNs) on large input graphs while preserving original performance.
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
Decentralized stochastic gradient descent (D-SGD) allows collaborative learning on massive devices simultaneously without the control of a central server.
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization
Graph Neural Networks (GNNs) have emerged as a powerful category of learning architecture for handling graph-structured data.
Contrastive Identity-Aware Learning for Multi-Agent Value Decomposition
Value Decomposition (VD) aims to deduce the contributions of agents for decentralized policies in the presence of only global rewards, and has recently emerged as a powerful credit assignment paradigm for tackling cooperative Multi-Agent Reinforcement Learning (MARL) problems.
Topology-aware Generalization of Decentralized SGD
Our theory indicates that the generalizability of D-SGD is positively correlated with the spectral gap, and can explain why consensus control in initial training phase can ensure better generalization.
