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Efficient Constant Optimization for Symbolic Regression with GPU-Accelerated Tree-Based Genetic Programming
and-cluster-computingdistributedg-1-6i-2-8machine-learningmathematical-softwareneural-and-evolutionary-computingparallel
Constant optimization refines the numerical coefficients of candidate expressions in tree-based genetic programming for symbolic regression. But its per-generation cost has led modern GPU-accelerated frameworks to omit it or restrict it to lightweight forms. We present a GPU-resident, batched Levenb
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