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Found 3 papers, 2 papers with code
Optimizing Memory Mapping Using Deep Reinforcement Learning
We also introduce a Reinforcement Learning agent, mallocMuZero, and show that it is capable of playing this game to discover new and improved memory mapping solutions that lead to faster execution times on real ML workloads on ML accelerators.
Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs
Large Neighborhood Search (LNS) is a combinatorial optimization heuristic that starts with an assignment of values for the variables to be optimized, and iteratively improves it by searching a large neighborhood around the current assignment.
Solving Mixed Integer Programs Using Neural Networks
Our approach constructs two corresponding neural network-based components, Neural Diving and Neural Branching, to use in a base MIP solver such as SCIP.
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