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Deep learning regularization: Prevent overfitting effectively explained

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...
EurekAlert!

Label attention meets deep learning: a novel model for ICD-11 automatic classification of Chinese EMRs

BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Frontiers

Advancing Deep Learning Frameworks for Enhanced Cervical Cancer Diagnosis, Staging and Treatment

Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...

DLSS 4.5 is now live — I tested Nvidia’s upscaler to see which model you should actually use

Nvidia's DLSS 4.5 is now available to all gamers, so I put it to the test to see whether it's worth using, and figure out ...