开课单位--卡内基梅隆大学

1
SysML: On System and Algorithm co-design and Automatic Machine Learning[SysML：系统与算法协同设计与自动机器学习]
  Eric P. Xing(卡内基梅隆大学) The rise of Big Data and AI computing has led to new demands for Machine Learning systems to learn complex models with millions to billions of paramet...
热度：36

2
A Dynamic Pipeline for Spatio-Temporal Fire Risk Prediction[时空火灾风险预测的动态管道]
  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：47

3
Clustering Applications at Yahoo![Yahoo！的群集应用程序！]
  Deepayan Chakrabarti(卡内基梅隆大学) Clustering Applications at Yahoo!
热度：24

4
AI Grand Challenges: Past, Present and Future[人工智能大挑战：过去、现在和未来]
  Ganesh Mani(卡内基梅隆大学) Innovative, bold initiatives that capture the imagination of researchers and system builders are often required to spur a field of science or technolo...
热度：87

5
A Quasi-experimental Estimate of the Impact of P2P Transportation Platforms on Urban Consumer Patterns[P2P交通平台对城市消费模式影响的准实验估计]
   Zhe Zhang(卡内基梅隆大学) With the pervasiveness of mobile technology and location-based computing, new forms of smart urban transportation, such as Uber & Lyft, peer-to-pe...
热度：23

6
Dense 3D Face Alignment from 2D Videos in Real-Time[根据 2D 视频实时进行密集 3D 人脸识别]
  Laszlo Attila Jeni(卡内基梅隆大学) Dense 3D Face Alignment from 2D Videos in Real-Time
热度：20

7
Data-Driven Approaches towards Malicious Behavior Modeling[数据驱动的恶意行为建模方法]
  Christos Faloutsos;Srijan Kumar(卡内基梅隆大学) The safety, reliability and usability of web platforms are often compromised by malicious entities, such as vandals on Wikipedia, bot connections on T...
热度：15

8
Feasibility and Pragmatics of Classifying Working Memory Load with an Electroencephalograph[用脑电图对工作记忆负荷进行分类的可行性和实用性]
  Scott E.Hudson(卡内基梅隆大学) We demonstrate high accuracies classifying working memory load using an electroencephalograph (EEG), even with little temporallag, not much training d...
热度：15

9
What can the world tell us about an image?[关于一幅图像，世界能告诉我们什么？]
  Alexei Efros(卡内基梅隆大学) What can the world tell us about an image?
热度：25

10
Learning Deep Boltzmann Machines[学习深度玻尔兹曼机]
  Ruslan Salakhutdinov(卡内基梅隆大学) Learning Deep Boltzmann Machines
热度：27