Graph representation learning aims at transforming graph data into meaningful low-dimensional vectors to facilitate the employment of machine learning and data mining algorithms designed for general ...

These algorithms mirror the architecture of human brains by building complex representations of information. They learn to understand environments by experiencing them, identify what seems to ...

Beijing, Feb. 05, 2024 (GLOBE NEWSWIRE) -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced ...

This library consists of various data prorcessing, graph factorization and embedding algorithms built around a common conceptual framework to enable quick construction of systems capable of learning ...

Our paper evaluates the proclaimed predictive performance of state-of-the-art inductive graph representation learning algorithms on highly imbalanced credit card transaction networks. More ...

Convex optimization is a key tool in computer science, with applications ranging from machine learning to operational research. Due to the fast growth of data sizes, the development of faster ...

The multi-view representation learning algorithm can provide an effective solution to the data stream clustering problem. The multi-view representation learning algorithm is a method of learning and.