报告人：Xiao Luo (Peking University)
时间：2020-10-23 12:00-13:30
地点：Room 1303, Sciences Building No. 1
各位数院研究生同学：
研究生学术午餐会是在学院领导的大力支持下，由研究生会负责组织的系列学术交流活动。
午餐会每次邀请一位同学作为主讲人，面向全院各专业背景的研究生介绍自己科研方向的基本问题、概念和方法，并汇报近期的研究成果和进展，是研究生展示自我、促进交流的学术平台。
研究生会已经举办了四十三期活动，我们将于2020年10月23日周五举办第四十四期学术午餐会活动，欢迎感兴趣的老师和同学积极报名参加。
报告人简介：tyc234cc 太阳成集团2017级直博研究生，导师为邓明华教授。主要研究方向为深度学习，生物信息学。曾获2019-2020国家奖学金，2019-2020（tyc234cc 太阳成集团）校长奖学金。
Abstract: Convolutional neural networks (CNNs) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. While previous studies have built a connection between CNNs and probabilistic models, simple models of CNNs cannot achieve sufficient accuracy on this problem. Recently, some methods of neural networks have increased performance using complex neural networks whose results cannot be directly interpreted. However, it is difficult to combine probabilistic models and CNNs effectively to improve DNA–protein binding predictions. In this article, we present a novel global pooling method: expectation pooling for predicting DNA–protein binding. Our pooling method stems naturally from the expectation maximization algorithm, and its benefits can be interpreted both statistically and via deep learning theory. Through experiments, we demonstrate that our pooling method improves the prediction performance DNA–protein binding. Our interpretable pooling method combines probabilistic ideas with global pooling by taking the expectations of inputs without increasing the number of parameters. We also analyze the hyperparameters in our method and propose optional structures to help fit different datasets. We explore how to effectively utilize these novel pooling methods and show that combining statistical methods with deep learning is highly beneficial, which is promising and meaningful for future studies in this field.
This is a joint work with Xinming Tu.
报名方式：请有意参加的同学于2020年10月22日（周四）中午12点前填写报名问卷，复制问卷链接https://www.wjx.cn/jq/94425158.aspx至浏览器或点击阅读原文进入问卷报名。
特别注意：如果您报名却没有参与活动，需要您自己承担已经购买的午餐费用。由于客观条件限制，本次午餐会的名额为40人，先报先得。
问卷如果填写成功即说明报名成功，请准时参加活动。如果临时有事不能参加请于10月22日中午12点前发邮件至smsxueshu@126.com。
如果问卷无法成功填写，说明报名人员已满，我们对难以成功报名的同学表示歉意。研究生会将继续探索午餐会的实现形式，争取更好地服务全体研究生同学。
注意：未经请假但未参加活动两次的同学禁止参加本学年全部午餐会活动。另外，请到场参加的同学不要无故早退，无故早退的同学也将被禁止参加本学年全部学术午餐会活动。
