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8040威尼斯·(Macau)官网工程研究学术论坛(第690期)

智能制造技术教育部重点实验室 学术论坛

报告题目:Introduction to Conformal Prediction: Application to Multi-label Classification

报告嘉宾:Wenge Guo Department of Mathematical Sciences New Jersey Institute of Technology, Newark, NJ, USA

报告时间:2024年7月4日下午3:00

报告地点:科技楼五楼521会议室

报告摘要:

Conformal prediction is a versatile statistical framework

that offers valid measures of uncertainty for predictions in supervised learning tasks. It ensures that prediction intervals or sets contain the true outcomes with a specified probability, thereby providing a robust measure of reliability. This methodology is particularly valuable in fields where precise uncertainty quantification is essential. In this talk, we will provide a comprehensive introduction to this interdisciplinary field, bridging machine learning and statistics. We will also explore the application of conformal prediction to multi-label classification, a complex task where each instance can be associated with multiple labels simultaneously.

嘉宾简介:

Wenge Guo is an Associate Professor of Statistics at the New Jersey Institute of Technology. He earned his PhD in Biostatistics from the University of Cincinnati and subsequently worked as a Research Fellow at the National Institute of Environmental Health Sciences for two years.

He serves on the editorial boards of three journals: Statistics & Probability Letters, PLOS ONE, and the Calcutta Statistical Association Bulletin. His primary research interests encompass Statistical Machine Learning, Multiple Testing, Selective Inference, and Statistical Methods for Clinical Trials.

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