开课单位--加州大学洛杉矶分校
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1
Learning Deep Structured Models[学习深度结构化模型]
  Liang-Chieh Chen(加州大学洛杉矶分校) Many problems in real-world applications involve predicting several random variables that are statistically related. Markov random fields (MRFs) are a...
热度:19

2
The Co-Evolution Model for Social Network Evolving and Opinion Migration[社会网络进化与意见迁移的协同进化模型]
  Yupeng Gu(加州大学洛杉矶分校) Almost all real-world social networks are dynamic and evolving with time, where new links may form and old links may drop, largely determined by the h...
热度:16

3
Integrating Context and Occlusion for Car Detection by Hierarchical And-Or Model[基于层次和或模型的汽车检测上下文与遮挡的集成]
  Bo Li (加州大学洛杉矶分校) This paper presents a method of learning reconfigurable hierarchical And-Or models to integrate context and occlusion for car detection. The And-Or mo...
热度:19

4
Learning Deep Network Representations with Adversarially Regularized Autoencoders[使用对抗正则化自动编码器学习深度网络表示]
  Wenchao Yu(加州大学洛杉矶分校) The problem of network representation learning, also known as network embedding, arises in many machine learning tasks assuming that there exist a sma...
热度:27

5
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks[NetWalk:一种灵活的动态网络异常检测深度嵌入方法]
  Wenchao Yu(加州大学洛杉矶分校) Massive and dynamic networks arise in many practical applications such as social media, security and public health. Given an evolutionary network, it ...
热度:21

6
Ranking-Based Clustering of Heterogeneous Information Networks with Star Network Schema[基于聚类的异构信息网络的星型网络架构排名]
  Yizhou Sun(加州大学洛杉矶分校) A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better u...
热度:69

7
On the Completeness of First-Order Knowledge Compilation for Lifted Probabilistic Inference[对一阶知识编译的完整性概率推理]
  Guy Van den Broeck(加州大学洛杉矶分校) Probabilistic logics are receiving a lot of attention today because of their expressive power for knowledge representation and learning. However, this...
热度:61

8
Informative Brain-Mind Feature Space[信息脑思维特征空间]
  Mark Cohen(加州大学洛杉矶分校) A wide variety of brain-derived signals presently are available to drive brain computer interface devices. These include the popular EEG recordings, m...
热度:77

10
Efficient Market Making via Convex Optimization & Connection to Online Learning[基于凸优化的有效做市&与在线学习的联系 ]
  Jenn Wortman Vaughan(加州大学洛杉矶分校) A prediction market is a financial market designed to aggregate information. To facilitate trades, prediction markets are often operated by automated ...
热度:63
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