Tag: hyperparameter optimization

Researchers combined a vision transformer with a convolutional network and tuned the pair using whale- and swarm-inspired algorithms, reaching 96.27 ...

Researchers have developed a crow-inspired, reference-free optimization framework that automatically tunes all hyperparameters of iterative CBCT reconstruction algorithms, delivering consistently ...

Researchers in India report that a Bayesian-optimized decision tree detects black hole attacks in RPL-based IoT networks with 98.71% accuracy, ...

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

Researchers in India have built an AI framework that classifies respiratory audio with over 96 percent accuracy, offering a non-invasive ...

Researchers in India have combined moth-inspired optimization, differential evolution and attention-based TabNet to predict vehicle maintenance failures with 97.6 percent ...

Researchers have developed a PSO-optimized stacking ensemble that estimates three-phase inverter voltages sensorlessly with errors below 1.6 percent across a ...

A matched-budget study of LoRA fine-tuning finds that genetic algorithms and other search optimizers offer no consistent advantage over well-tuned ...

Researchers trained five machine learning models on 3,185 measurements to predict the refractive index of surfactant-containing lithium bromide solutions with ...

Researchers in South Korea have developed a temporal convolutional network that forecasts dam storage six months in advance, doubling the ...