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Methods/Random Search

Random Search

GeneralIntroduced 2000256 papers

Description

Random Search replaces the exhaustive enumeration of all combinations by selecting them randomly. This can be simply applied to the discrete setting described above, but also generalizes to continuous and mixed spaces. It can outperform Grid search, especially when only a small number of hyperparameters affects the final performance of the machine learning algorithm. In this case, the optimization problem is said to have a low intrinsic dimensionality. Random Search is also embarrassingly parallel, and additionally allows the inclusion of prior knowledge by specifying the distribution from which to sample.

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Papers Using This Method

Regular Tree Search for Simulation Optimization2025-06-21 Learning Extrapolative Sequence Transformations from Markov Chains2025-05-26 Few-Shot Test-Time Optimization Without Retraining for Semiconductor Recipe Generation and Beyond2025-05-21 OPO: Making Decision-Focused Data Acquisition Decisions2025-04-21 A Case Study on Evaluating Genetic Algorithms for Early Building Design Optimization: Comparison with Random and Grid Searches2025-04-10 Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework2025-03-26 A stochastic gradient descent algorithm with random search directions2025-03-25 Learning Linear Block Codes with Gradient Quantization2025-03-20 Multi-Target Radar Search and Track Using Sequence-Capable Deep Reinforcement Learning2025-02-19 T-SCEND: Test-time Scalable MCTS-enhanced Diffusion Model2025-02-04 The M-factor: A Novel Metric for Evaluating Neural Architecture Search in Resource-Constrained Environments2025-01-29 Multi-Objective Reinforcement Learning for Power Grid Topology Control2025-01-27 Sample complexity of data-driven tuning of model hyperparameters in neural networks with structured parameter-dependent dual function2025-01-23 How Toxic Can You Get? Search-based Toxicity Testing for Large Language Models2025-01-03 HyperQ-Opt: Q-learning for Hyperparameter Optimization2024-12-23 Stalling in Space: Attractor Analysis for any Algorithm2024-12-20 Generating Critical Scenarios for Testing Automated Driving Systems2024-12-03 LAMBDA: Covering the Multimodal Critical Scenarios for Automated Driving Systems by Search Space Quantization2024-11-30 Randomized-Grid Search for Hyperparameter Tuning in Decision Tree Model to Improve Performance of Cardiovascular Disease Classification2024-11-27 Testing the Efficacy of Hyperparameter Optimization Algorithms in Short-Term Load Forecasting2024-10-19