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Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem
This suggests that our method offers a promising avenue for future research and practical application in the field of job shop scheduling problems.
Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling
Various approaches of active learning have been proposed in the literature, however, they either focus on exploration or exploitation in the design space.
Gene selection with guided regularized random forest
In RRF the features are evaluated on a part of the training data at each tree node.
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