Tag: neural architecture search

A neural architecture search framework called CMS-NAS automatically evolves hybrid convolutional, Mamba and spiking network designs for lightweight, accurate EEG-based ...

A new deep learning framework that passively reads smartphone sensor data from college students can detect depression and stress, but ...

A new framework combining a discourse-aware Context-Aware Transformer with a dynamically perturbed fox-inspired optimization algorithm achieves significant gains in coherent ...

Researchers have reformulated multi-class classification as a many-objective problem in which each class is a separate goal, using evolutionary neural ...

Researchers at NIT Durgapur compared NSGA-II, MOSA, and Bayesian optimization for designing tiny keyword spotting models, finding MOSA most reliable ...

A hybrid compression framework combining knowledge distillation, quantization-aware training, and dynamic inference achieves 92.3 percent semantic accuracy at 1.5 watts ...

Researchers have developed xAutoGA, an open-source automated deep learning platform that uses a genetic algorithm, natural-selection visualizations, rule extraction, and ...

A new survey in Artificial Intelligence Review unifies graph structure learning and automated graph neural architecture search into a single ...

A new systematic review argues that training-free neural architecture search can slash the enormous computational cost of AI model design ...