开课单位--卡内基梅隆大学

21
Overview of decoding of mental states and processes[心理状态和过程解码概述]
  Tom Mitchell(卡内基梅隆大学) Overview of decoding of mental states and processes
热度：19

22
Discriminative Graphical Models for Protein Quaternary Structure Motif Detection[蛋白质四元结构Motif检测的判别图形模型]
  Yan Liu(卡内基梅隆大学) Discriminative Graphical Models for Protein Quaternary Structure Motif Detection
热度：18

23
Generalized Score Functions for Causal Discovery[因果发现的广义评分函数]
  Biwei Huang(卡内基梅隆大学) Discovery of causal relationships from observational data is a fundamental problem. Roughly speaking, there are two types of methods for causal discov...
热度：32

24
Rare Query Expansion Through Generative Adversarial Networks in Search Advertising[搜索广告中通过生成对抗网络的罕见查询扩展]
  Mu-Chu Lee(卡内基梅隆大学) Generative Adversarial Networks (GAN) have achieved great success in generating realistic synthetic data like images, tags, and sentences. We explore ...
热度：22

25
PrivOnto: a Semantic Framework for the Analysis of Privacy Policies[PrivOnto：隐私政策分析的语义框架]
  Alessandro Oltramari(卡内基梅隆大学) Privacy policies are intended to inform users about the collection and use of their data by websites, mobile apps and other services or appliances the...
热度：14

26
Link-PLSA-LDA: A new unsupervised model for topics and influence of blogs[链接PLSA LDA：博客主题和影响力的新的无监督模型]
  Ramesh Nallapati(卡内基梅隆大学) Link-PLSA-LDA: A new unsupervised model for topics and influence of blogs
热度：15

27
A Dynamic Pipeline for Spatio-Temporal Fire Risk Prediction[火灾风险时空预测的动态管道]
  Jessica Lee(卡内基梅隆大学) Recent high-profile fire incidents in cities around the world have highlighted gaps in fire risk reduction efforts, as cities grapple with fewer resou...
热度：25

28
Elo-MMR: A Rating System for Massive Multiplayer Competitions[Elo MMR：大型多人比赛的评分系统]
  Aram Ebtekar(卡内基梅隆大学) Elo-MMR: A Rating System for Massive Multiplayer Competitions
热度：38

29
Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations[对话进展顺利：量化和预测在线对话中的亲社会结果]
   Jiajun Bao(卡内基梅隆大学) Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations
热度：25

30
Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning[基于机器学习的DOM XSS漏洞检测的轻量级混合方法]
  Clement Fung(卡内基梅隆大学) Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning
热度：32