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 ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Brandee Gruener is a digital editor and writer with 20 years of experience. Her articles on gardening, homes, food, and health have appeared in Hunker, American Gardener, and other national and ...

Policy gradient methods have significantly advanced the reasoning capabilities of LLMs, particularly through RL. A key tool in stabilizing these methods is Kullback-Leibler (KL) regularization, which ...

1 Department of Environmental Sciences, Jahangirnagar University, Dhaka, Bangladesh 2 Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden ...

According to Kevin Zakka (@kevin_zakka), a new kinetic energy regularization task has been integrated into the Mink AI library, available in version 0.0.11 (source: Twitter, May 23, 2025). This update ...

Quantum cryptography has emerged as a radical research field aimed at mitigating various security threats in modern communication systems. The integration of Quantum Machine Learning (QML) protocols ...

ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...