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Found 2 papers, 2 papers with code
X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation
Tensor graph superoptimisation systems perform a sequence of subgraph substitution to neural networks, to find the optimal computation graph structure.
RLFlow: Optimising Neural Network Subgraph Transformation with World Models
Our proposed approach RLFlow can learn to perform neural network subgraph transformations, without the need for expertly designed heuristics to achieve a high level of performance.
Model-based Reinforcement Learning
reinforcement-learning
+1
