Recently, a research team from Hokkaido University made significant progress in the complexity study of the Hitting Geodesic Intervals (HGI) problem. The HGI problem aims to find a small set of ...

Towards efficient algorithms on compressed graph databases Abstract: The speed of algorithms on massive graphs depends on the size of the given data. Grammar-based compression is a technique to ...

In the field of natural language processing, text classification, as a basic task, has important research value and application prospects. Traditional text classification methods usually rely on ...

The Δ-Motif algorithm leverages open-source libraries such as Pandas and Numpy, and achieves parallel processing on GPUs through NVIDIA's RAPIDS. According to benchmark tests, the algorithm's speed is ...

Link prediction is a crucial task in network analysis, widely used in areas like social network recommendation, knowledge graph completion, and bioinformatics. Traditional link prediction methods ...

In an era where autonomous systems demand pinpoint accuracy, navigation algorithms face a tough trade-off between precision and speed.

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of ...

Jakub Pachocki，我们的首席科学家，曾以「不知疲倦」来形容 Szymon，这或许也是他们二人共同的写照。多年来，我亲眼见证了这对传奇搭档如何完美互补，解决了一个又一个难题。他们是 OpenAI 的基石，是推动 AI ...

Google DeepMind and Intrinsic developed AI that uses graph neural networks and reinforcement learning to automate multi-robot ...