开课单位--卡内基梅隆大学

161
Minimax Localization of Structural Information in Large Noisy Matrices[大噪声矩阵中结构信息的极小极大局部化]
  Sivaraman Balakrishnan(卡内基梅隆大学) We consider the problem of identifying a sparse set of relevant columns and rows in a large data matrix with highly corrupted entries. This problem of...
热度：16

162
On a Theory of Similarity Functions for Learning and Clustering[相似度函数的理论学习和聚类]
  Avrim Blum(卡内基梅隆大学) Kernel methods have become powerful tools in machine learning. They perform well in many applications, and there is also a well-developed theory of wh...
热度：28

163
Doulion: Counting Triangles in Massive Graphs with a Coin[Doulion:在大规模计算三角形图中使用硬币]
  Tsourakakis Charalampos E(卡内基梅隆大学) Counting the number of triangles in a graph is a beautiful algorithmic problem which has gained importance over the last years due to its significant ...
热度：26

164
Leveraging Temporal Dynamics of Document Content in Relevance Ranking[利用相关主题中文档内容的时间动态]
  Jonathan Elsas(卡内基梅隆大学) Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a st...
热度：16

165
REGO: Rank-based estimation of Renyi information using Euclidean graph optimization[基于“政府改造”:等级的评估使用欧几里德Renyi信息图的优化]
  Barnabás Póczos(卡内基梅隆大学) We propose a new method for a non-parametric estimation of Renyi and Shannon information for a multivariate distribution using a corresponding copula,...
热度：14

166
On the Estimation of alpha-Divergences[关于α分歧的估计]
  Barnabás Póczos(卡内基梅隆大学) We propose new nonparametric, consistent Renyi-alpha and Tsallis-alpha divergence estimators for continuous distributions. Given two independent and i...
热度：12

167
Mining Billion-node Graphs: Patterns, Generators and Tools[挖掘十亿节点图：模式、生成器和工具]
  Christos Faloutsos(卡内基梅隆大学) What do graphs look like? How do they evolve over time? How to handle a graph with a billion nodes? We present a comprehensive list of static and temp...
热度：40

168
Sample Complexity for Multiresolution ICA[多分辨率ICA的样本复杂度]
  Doru Balcan(卡内基梅隆大学)  Sample Complexity for Multiresolution ICA
热度：65

169
Crawl Ordering by Search Impact[搜索影响下的爬行排序]
  Sandeep Pandey(卡内基梅隆大学)  Crawl Ordering by Search Impact
热度：42

170
ICWSM 2009 Opening Remarks[网络博客与社交媒体会议 2009开幕词]
  William Cohen(卡内基梅隆大学) 3rd International AAAI Conference on Weblogs and Social Media (ICWSM), San Jose 2009
热度：23