Recently, a research team from the Rudolf Technology Center in Slovenia proposed a new method to optimize the sparse subgraph problem, which has wide applications in fields such as network analysis ...

The constant scaling of AI applications and other digital technologies across industries is beginning to tax the energy grid ...

Sparse matrices are fundamental to many computational problems, and their efficient representation in quantum computing is crucial for unlocking the potential of quantum algorithms. The core ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

where the output is not from a fixed vocabulary, but a sequence of pointers to elements from the input. Main idea: Instead of producing an output token from a fixed-size vocabulary, the model points ...

SoftBank conducted a proof-of-concept experiment in Tokyo using an Ising machine, a type of quantum computing technology, to optimize radio base station settings. As a result, in 5G communications ...

The Neural Combinatorial Optimization Library (NCOLib) is an accessible software library designed to simplify the application of neural network models and deep learning algorithms to approximately ...

Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...

Shenzhen, May 14, 2025 (GLOBE NEWSWIRE) -- MicroAlgo Inc. Announces Research on Quantum Information Recursive Optimization (QIRO) Algorithm, for Combinatorial Optimization Problems to Expand and Solve ...