Regularization is a technique used in machine learning to prevent overfitting, which is a situation where a machine learning model performs well on training data but poorly on unseen data (test data).

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 ...

In the realm of quantum machine learning, MicroAlgo introduces a novel quantum regularization strategy called Quantum Entanglement Regularization (QER).

Novel Regularization Strategy to Enhance Training Stability and Generalization Capability: In classical machine learning, regularization methods are widely used to prevent model overfitting.

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (MLGO) (the "Company" or "MicroAlgo") announced today the launch of their latest classifier auto-optimization technology based on ...