Machine learning is an integral part of high stakes decision making in a broad swath of human-computer interactions. You apply for a job. You submit a loan application. Algorithms determine who ...

Just as people from different countries speak different languages, AI models also create various internal "languages"—a unique set of tokens understood only by each model. Until recently, there was no ...

Apart from simple diagnosis, the study takes an important step toward predictive health monitoring by modeling the risk of ...

The rise of FML allows systems to become progressively more intelligent and autonomous by using on-device data and sharing only encrypted model updates.

In the current era of big data, the volume of information continues to grow at an unprecedented rate, giving rise to the crucial need for efficient ...

As companies rush to adopt new AI solutions, business leaders must understand the different types and how AI compares to ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

IoT-based sensors, when deployed within biofloc tanks, can continuously track critical parameters such as dissolved oxygen ...

Support Vector Machine (SVM) is one of the most widely used algorithms for solving classification and regression problems. SVM parameters such as the kernel and the penalty (C) parameters greatly ...

This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning to solve ...