A graph transformer with RL stabilizations is the first to exceed benchmarks for dynamic RMSA, supporting up to 13% more traffic load on networks up to 143 nodes.
Podracer architectures for scalable Reinforce- ment Learning
2 Pith papers cite this work. Polarity classification is still indexing.
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Delightful Policy Gradient gates updates with advantage times surprisal to suppress rare failures while preserving rare successes in distributed RL with stale or buggy data.
citing papers explorer
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Graph Transformers and Stabilized Reinforcement Learning for Large-Scale Dynamic Routing Modulation and Spectrum Allocation in Elastic Optical Networks
A graph transformer with RL stabilizations is the first to exceed benchmarks for dynamic RMSA, supporting up to 13% more traffic load on networks up to 143 nodes.
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Delightful Distributed Policy Gradient
Delightful Policy Gradient gates updates with advantage times surprisal to suppress rare failures while preserving rare successes in distributed RL with stale or buggy data.