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Found 3 papers, 0 papers with code
Supervised Permutation Invariant Networks for Solving the CVRP with Bounded Fleet Size
Learning to solve combinatorial optimization problems, such as the vehicle routing problem, offers great computational advantages over classical operations research solvers and heuristics.
Improving Hyperparameter Optimization by Planning Ahead
Hyperparameter optimization (HPO) is generally treated as a bi-level optimization problem that involves fitting a (probabilistic) surrogate model to a set of observed hyperparameter responses, e. g. validation loss, and consequently maximizing an acquisition function using a surrogate model to identify good hyperparameter candidates for evaluation.
Hyperparameter Optimization
Model-based Reinforcement Learning
+4
Atomic Compression Networks
Compressed forms of deep neural networks are essential in deploying large-scale computational models on resource-constrained devices.
