【Coll.0629】Prof. Jun Zhu: Learning with Deep Generative Models
时间:2017-06-20  浏览:311次

Title: Learning with Deep Generative Models

Abstract: Deep generative models are flexible tools on revealing the latent structures underlying complex data and performing “top-down” inference to generate samples. In this talk, I will present some results on learning with deep generative models, including discriminative learning for high-accuracy prediction in supervised and semi-supervised settings, a new conditional moment-matching criterion to estimate the parameters, and ZhuSuan--a GPU library to support probabilistic programming and efficient inference. 

朱军,清华大学计算机系长聘副教授、卡内基梅隆大学兼职教授,智能技术与系统国家重点实验室副主任。担任顶级期刊IEEE PAMIArtificial Intelligence编委,顶级会议ICML 2014地区联合主席, ICML (2014-2017)NIPS (2013, 2015)IJCAI20152017)、AAAI2016, 2017)等领域主席。获CCF青年科学家奖、国家优青基金、中创软件人才奖等,入选国家“万人计划”青年拔尖人才计划和IEEE Intelligent Systems AI’s 10 to Watch

报告时间:2017-06-29 10:30 - 11:30