2023 IEEE International Conference on Data Mining Workshops (ICDMW) 1–4 December 2023, Shanghai, China

Shanghai : IEEE Computer Society, 2023.

Under the general editorship: J. Wang, Y. He, T. Dinh, C. Grant, M. Qiu, W. Pedrycz

The IEEE International Conference on Data Mining (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, and applications. ICDM draws researchers, application developers, and practitioners from a wide range of data mining related areas such as big data, deep learning, pattern recognition, statistical and machine learning，databases, data warehousing, data visualization, knowledge-based systems, and high-performance computing. By promoting novel, high-quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to advance the state-of-the-art in data mining.

Chapters

Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust

Erlygin L., Zholobov V., Baklanova V. et al., , in: 2023 IEEE International Conference on Data Mining Workshops (ICDMW) 1–4 December 2023, Shanghai, China.: Shanghai: IEEE Computer Society, 2023. P. 1247–1258.

Machine learning models play a vital role in time series forecasting. These models, however, often overlook an important element: point uncertainty estimates. Incorporating these estimates is crucial for effective risk management, informed model selection, and decision-making.To address this issue, our research introduces a method for uncertainty estimation. We employ a surrogate Gaussian process regression model. ...

Added: March 20, 2024

Keywords: data mining, machine learning, deep learning, mathematical and statistical methods