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Found 4 papers, 0 papers with code
An Evolutionary Network Architecture Search Framework with Adaptive Multimodal Fusion for Hand Gesture Recognition
To automatically adapt to various datasets, the ENAS framework is designed to automatically search a MHGR network with appropriate fusion positions and ratios.
Multiple Population Alternate Evolution Neural Architecture Search
Specifically, the global search space requires a significant amount of computational resources and time, the scalable search space sacrifices the diversity of network structures and the hierarchical search space increases the search cost in exchange for network diversity.
G-EvoNAS: Evolutionary Neural Architecture Search Based on Network Growth
The process begins from a shallow network, grows and evolves, and gradually deepens into a complete network, reducing the search complexity in the global space.
Combining Kernelized Autoencoding and Centroid Prediction for Dynamic Multi-objective Optimization
Evolutionary algorithms face significant challenges when dealing with dynamic multi-objective optimization because Pareto optimal solutions and/or Pareto optimal fronts change.
