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KDD 2024Workshop Summaries

3rd Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM)

Xujiang Zhao, Chen Zhao 0010, Feng Chen 0001, Jin-Hee Cho, Wei Hua, Haifeng Chen

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3637528.3671496 ↗

摘要

Uncertainty reasoning and quantification play a critical role in decision making across various domains, prompting increased attention from both academia and industry. As real-world applications become more complex and data-driven, effectively handling uncertainty becomes paramount for accurate and reliable decision making. This workshop focuses on the critical topics of uncertainty reasoning and quantification in decision making. It provides a platform for experts and researchers from diverse backgrounds to exchange ideas on cutting-edge techniques and challenges in this field. The interdisciplinary nature of uncertainty reasoning and quantification, spanning artificial intelligence, machine learning, statistics, risk analysis, and decision science, will be explored. The workshop aims to address the need for robust and interpretable methods for modeling and quantifying uncertainty, fostering reasoning decision-making in various domains. Participants will have the opportunity to share research findings and practical experiences, promoting collaboration and advancing decision-making practices under uncertainty.