Conference: Toward Explainable, Reliable, and Sustainable Machine Learning for Signal and Data Science

会议：迈向信号和数据科学的可解释、可靠和可持续的机器学习

• 批准号: 2321063
• 负责人: Min Wu
• 金额: $ 4.99万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321063&HistoricalAwards=false
• 关键词: Conference; Toward; Explainable; Reliable; Sustainable; Conference; Toward; Explainable; Reliable; Sustainable

The fast-growing areas of artificial intelligence (AI) and machine learning (ML), especially in the area of deep models, are bringing new ways and tools of solving problems beyond the traditional paradigms. They offer new perspectives and also prompt challenges and open questions in the areas of signal processing and data science. This workshop aims at bringing together experts from academia, industry, government agencies, and professional societies to discuss research challenges, opportunities, and potential pathways forward and collaborative efforts needed toward explainable, reliable, and sustainable machine learning for signal and data science. The workshop will be held in College Park, MD, on March 20-21, 2023, to foster convergence research in AI/ML. The workshop will initiate a dialogue and foster open and constructive exchanges of a group of leading experts with complementary expertise and perspectives. It is envisioned that this two-day workshop will feature keynote presentations, panel discussions, as well as break-out and summary sessions; participants from a wide range of background will be engaged, such as signal sensing and processing, data science, machine learning, computer vision, speech and natural language, control theory and system, information theory, and more. Discussions and collaborations facilitated by the workshop will help shape the paradigm of research and graduate education in the new era of AI, and pave a pathway forward to the research advancement and talent training in machine learning that can benefit society in sound, reliable, and sustainable ways.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

人工智能（AI）和机器学习（ML）的快速增长领域（尤其是在深层模型领域）正在带来新的方法和工具，以解决传统范式之外的问题。 他们提供了新的观点，并在信号处理和数据科学领域引起挑战和开放问题。 该研讨会旨在将来自学术界，行业，政府机构和专业社会的专家汇集在一起​​，讨论研究挑战，机遇以及潜在的途径，并为信号和数据科学提供可解释，可靠和可持续的机器学习所需的努力。该研讨会将于2023年3月20日至21日在马里兰州大学公园举行，以促进AI/ML的融合研究。该研讨会将启动对话，并促进具有互补专业知识和观点的一群领先专家的开放和建设性交流。可以预见的是，为期两天的研讨会将以主题演讲，小组讨论以及分类和摘要为特色。将参与来自广泛背景的参与者，例如信号传感和处理，数据科学，机器学习，计算机视觉，语音和自然语言，控制理论和系统，信息理论等。 研讨会促进的讨论和合作将有助于塑造AI的新时代的研究和研究生教育的范式，并在机器学习方面的研究进步和人才培训铺平了途径，可以使社会上的社会受益，可靠，可持续的道路上的社会。这项奖项通过评估律师的构成师的构成师的范围，这是对NSF的审查的影响力的审查。