Machine learning has revolutionised the field of classification in numerous domains, providing robust tools for categorising data into discrete classes. However, many practical applications, such ...

In a breakthrough for artificial intelligence (AI) and finance, computer scientists from Texas A&M University have developed a machine learning based method called Symbolic Modeling to handle ...

The complexity and size of software systems has increased to the extent that traditional manual development and maintenance ...

Neurosymbolic AI is a combination of symbolic AI and neural networks and is well-suited for commercial applications. Symbolic AI can process abstract concepts and make deductive judgments.

The study provides both the theoretical foundations and empirical evidence for a new family of machine learning (ML) methods that not only compete with but outperform state-of-the-art statistical ...

Beyond performance, the framework breaks new ground in its unification of symbolic reasoning and statistical learning.

The study provides both the theoretical foundations and empirical evidence for a new family of machine learning (ML) methods that not only compete with but outperform state-of-the-art statistical ...

MicroAlgo's classifier auto-optimization technology significantly reduces computational complexity through deep optimization of the core circuit.