Scientists Present New Solution to Imbalanced Learning Problem
Specialists at the HSE Faculty of Computer Science and Sber AI Lab have developed a geometric oversampling technique known as Simplicial SMOTE. Tests on various datasets have shown that it significantly improves classification performance. This technique is particularly valuable in scenarios where rare cases are crucial, such as fraud detection or the diagnosis of rare diseases. The study's results are available on ArXiv.org, an open-access archive, and will be presented at the International Conference on Knowledge Discovery and Data Mining (KDD) in summer 2025 in Toronto, Canada.
Drivers of Progress and Sources of Revenue: The Role of Universities in Technology Transfer
In the modern world, the effective transfer of socio-economic and humanities-based knowledge to the real economy and public administration is essential. Universities play a decisive role in this process. They have the capability to unite diverse teams and, in partnership with the state and businesses, develop and enhance advanced technologies.