开课单位--康奈尔大学

1
Information Elicitation[获取信息]
  Yichi Zhang(康奈尔大学) Information Elicitation
热度：37

2
From Word Embeddings To Document Distances[从词嵌入到文档距离]
  Matt J. Kusner(康奈尔大学) We present the Word Mover’s Distance (WMD), a novel distance function between text documents. Our work is based on recent results in word embedd...
热度：14

3
Compressing Neural Networks with the Hashing Trick[使用哈希技巧压缩神经网络]
  Kilian Q. Weinberger(康奈尔大学) As deep nets are increasingly used in applications suited for mobile devices, a fundamental dilemma becomes apparent: the trend in deep learning is to...
热度：23

4
Clustered Graph Randomization: Network Exposure to Multiple Universes[聚类图随机化：多个普遍性下的网络暴露]
  Johan Ugander(康奈尔大学) A/B testing is a standard approach for evaluating the effect of online experiments; the goal is to estimate the `average treatment effect' of a ne...
热度：30

5
Bayesian Neural Nets[贝叶斯神经网络]
  Andrew Gordon Wilson(康奈尔大学) Bayesian Neural Nets
热度：75

6
Efficient Active Learning[高效主动学习]
  Nikos Karampatziakis(康奈尔大学) We present and analyze an active learning algorithm that is theoretically sound in an agnostic setting, empirically effective, and as efficient as sta...
热度：25

7
Opinion Dynamics with Varying Susceptibility to Persuasion[具有不同说服易感性的意见动力学]
  Rediet Abebe(康奈尔大学) A long line of work in social psychology has studied variations in people’s susceptibility to persuasion – the extent to which they are wi...
热度：41

8
Additive Groves of Regression Trees[回归树的加法群]
  Daria Sorokina(康奈尔大学) Additive Groves of Regression Trees
热度：34

9
DBToaster: Aggressive Compilation Techniques for Online Aggregation[DBToaster：用于在线聚合的攻击性编译技术]
  Christoph Koch(康奈尔大学) DBToaster: Aggressive Compilation Techniques for Online Aggregation
热度：24

10
Sequences of Sets[集合的序列]
  Austin R. Benson(康奈尔大学) Sequences of Sets
热度：28