FAI-Seminar

FAI-Seminar

FAI-Seminar (International Seminar on Foundational Artificial Intelligence) 是一个以人工智能基础为主题的线上中文研讨班。在每一次研讨班中,会有一位讲者分享其近期的工作。欢迎大家来玩!

  • 主题:人工智能基础(以机器学习理论为主,也有有趣的应用工作)

  • 时间:每周五上午10:00 - 11:00 (北京时间)

  • 参加方式:请关注公众号【人工智能基础研究】发送【FAI】加入微信群

  • 官方账号:请关注B站 @FAI-Seminar收看录播/直播,微信公众号

  • 语言:中文

  • 官方手册: 基础信息; 观众须知; 讲者须知


    • 公众号:人工智能基础研究

    最近新闻 / News!


    Update: 2023.10.23

  • 第三轮regular talk信息已发布!

  • 第二轮全部talk已更新完毕,感谢大家的支持!

  • 新的栏目FAI-Reading ,欢迎大家来玩!

  • 视频播放总数已破9万,感谢大家的支持!
  • 日程安排 / Schedule


    2023 R03
    Time Speaker Talk Title Talk Info Paper Video
    Special Talk 胡威(UMich)
    11/10 陈乐偲(清华大学) Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles Talk Info [1] B站
    11/17 张博航(北京大学) Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective Talk Info [1] B站
    11/24 顾欣然(清华大学) A Quadratic Synchronization Rule for Distributed Deep Learning Talk Info [1] B站
    12/1 石佳欣(DeepMind) MultiresConv: From Wavelet Theory to Long Context Modeling with Neural Networks Talk Info [1]
    12/8 范凤磊(香港中文大学)
    12/15 NeurIPS break
    12/22 刘冰彬(CMU)
    12/29 温凯越(清华大学)
    1/5 游凯超(清华大学)

    2023 R02
    Time Speaker Talk Title Paper Video
    (Special)09/15 李志远(Stanford) The Generalization Benefit of Flatnes Regularization [1][2] B站
    06/23 张博航(北京大学) Understanding the Expressivity of Subgraph-based GNNs for Graph Learning [1] B站
    06/30 罗胜杰(北京大学) One Transformer Can Understand Both 2D & 3D Molecular Data [1] B站
    07/07 刘子鸣(MIT) Intelligence from hunger [1], [2] B站
    07/14 马鉴昊(UMich) Robust Sparse Mean Estimation [1] B站
    07/21 金及凯(北京大学) Minimax optimal operator learning [1] B站
    07/28 ICML break
    08/04 王博涵(中国科学技术大学) When and Why Momentum Accelerates SGD [1] B站
    08/11 滕佳烨(清华大学) Predictive inference with feature conformal prediction [1] B站
    08/18 蔡天乐(Princeton) Large Language Models as Tool Makers [1] B站

    2023 R01
    Time Speaker Talk Title Paper Video
    (Special) 05/26 张景昭(清华大学) Two Phases of Scaling Laws for Nearest Neighbor Classifiers [1] B站
    03/03 张鼎怀(Mila) GFlowNets: Exploration for Probabilistic Inference [1],[2],[3],[4] B站
    03/10 顾欣然(清华大学) Why (and When) does Local SGD Generalize Better than SGD [1] B站
    03/17 王博涵(中国科学技术大学) Provable Benefit of Adaptivity in ADAM [1] B站
    03/24 温凯越(清华大学) How Does Sharpness-Aware Minimization Minimize Sharpness? [1] B站
    03/31 张博航(北京大学) Rethinking the Expressive Power of GNNs via Graph Biconnectivity [1] (ICLR 2023 Outstanding Paper) B站
    04/07 马鉴昊(UMich) Escaping Saddle Points Or Not? [1], [2] B站
    04/14 陈乐偲(复旦大学) On Bilevel Optimization without Lower-level Strong Convexity [1] B站
    04/21 黄凯旋(Princeton) Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data [1] B站
    04/28 戴言(清华大学) Variance-Aware Sparse Linear Bandits [1] B站

    组织者 / Organizers

    贡献者 / Contributors

    特邀嘉宾 / Invited Guests

    协办单位 / Universities

    合作组织 / Partners

    • AI TIME 论道
      (公众号)
    • 轻松参会
      (公众号)
    • 蔻享学术
      (公众号)