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讲座预告

1月16日:Enhancing Deep Learning with Structures

  • 发表日期:2018-01-12 【 【打印】【关闭】
  •   模式识别学术大讲堂 

      

    Advanced Lecture Series in Pattern Recognition 

           (TITLE)Enhancing Deep Learning with Structures 

       (SPEAKER)Assoc. Prof. Le Song (Georgia Institute of Technology) 

       (CHAIR) Dr. Yanming Zhang 

           (TIME)10:30am, January 16 (Tuesday), 2018 

           (VENUE)No.1 Conference Room (3rd floor), Intelligence Building 

      报告摘要(ABSTRACT): 

      What has made deep learning models so effective? Is it the depth of the models or something else? How can we understand deep learning better and make it even more effective? In this talk, I will argue that the structure of a deep learning model and the landscape of the optimization problem are critically important for the success of such as a model.  I will present both empirical and theoretical evidence for understanding these structure aspects of deep learning, and show that following these findings we can design novel and state-of-the-art deep learning models for a diverse range of applications including face recognition, risk management for Fintech, reasoning over dynamic knowledge graphs, and algorithm design. 

      报告人简介(BIOGRAPHY): 

      宋乐是佐治亚理工大学计算科学与工程系终身副教授,机器学习中心副主任。他于2008年在Alex Smola的指导下从悉尼大学和NICTA获得机器学习博士学位。2008年至2011年间,在卡内基梅隆大学机器学习系Eric XingCarlos Guestrin的指导下进行了博士后研究。在2011年加入佐治亚理工学院之前,他曾是一名Google的科学家效力于Fernando Pereira 的机器学习部门。他的主要研究方向是核函数和深度学习的嵌入方法,机器学习的大规模算法和高效系统, 以及静态和动态网络分析,人工智能,社会科学,计算生物学等跨学科领域里的大规模复杂问题的建模和求解。他获得过很多机器学习方面的顶级国际奖项,包括NIPS’17机器学习与材料科学研讨会最佳论文奖,Recsys'16深度学习与推荐系统研讨会最佳论文奖,AISTATS'16最佳学生论文奖,IPDPS'15最佳论文奖,美国国家自然基金会NSF’14杰出青年奖,NIPS'13优秀论文奖和ICML'10最佳论文奖。历任ICMLNIPSAISTATSAAAIIJCAI等机器学习和AI顶尖会议的领域主席,也是机器学习顶尖杂志JMLRIEEE TPAMI的副主编。 

    承办单位:模式识别国家重点实验室