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NeurIPS 2020观察与分析
引用本文:林宙辰,王奕森.NeurIPS 2020观察与分析[J].中国图象图形学报,2021,26(2):229-244.
作者姓名:林宙辰  王奕森
作者单位:北京大学信息科学技术学院机器感知与智能教育部重点实验室, 北京 100871
摘    要:神经信息处理系统大会(Conference on Neural Information Processing Systems,NeurIPS)是机器学习领域的顶级会议,在中国计算机学会(China Computer Federation,CCF)推荐国际学术会议中被评为人工智能领域的A类会议,一直广受关注。NeurIPS 2020收到了创纪录的9 467篇投稿,最终录用1 898篇论文。收录的论文涵盖了人工智能的各种主题,包括深度学习及其应用、强化学习与规划、纯理论研究、概率方法、优化及机器学习与社会等。本文回顾了NeurIPS 2020的亮点及论文录用情况,详细解读了特邀报告、最佳论文、口头报告及部分海报论文,希望能帮助读者快速了解NeurIPS 2020的盛况。

关 键 词:人工智能  机器学习  深度学习  强化学习  理论  优化  学术会议  NeurIPS  2020
收稿时间:2020/12/21 0:00:00
修稿时间:2020/12/23 0:00:00

Report of NeurIPS 2020
Lin Zhouchen,Wang Yisen.Report of NeurIPS 2020[J].Journal of Image and Graphics,2021,26(2):229-244.
Authors:Lin Zhouchen  Wang Yisen
Affiliation:Key Laboratory of Machine Perception(MoE), School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
Abstract:The Conference on Neural Information Processing Systems (NeurIPS), as a top-tier conference in the field of machine learning and also a China Computer Federation(CCF)-A conference, has been receiving lots of attention. NeurIPS 2020 received a record-breaking 9 467 submissions, and finally accepted 1 898 papers, which covered various topics of artificial intelligence(AI), such as deep learning and its applications, reinforcement learning and planning, theory, probabilistic methods, optimization, and the social aspect of machine learning. In this paper, we first reviewed the highlights and statistical information of NeurIPS 2020, for example, using GatherTown (each attendee is represented by a cartoon character) to improve the experience of immersive interactions with each other. Following that, we summarized the invited talks which covered multiple disciplines such as cryptography, feedback control theory, causal inference, and biology. Moreover, we provide a quick review of best papers, orals and some interesting posters, hoping to help readers have a quick glance over NeurIPS 2020.
Keywords:artificial intelligence(AI)  machine learning  deep learning  reinforcement learning  theory  optimization  academic conference  NeurIPS 2020
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