图 书 馆开课单位--卡内基梅隆大学
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6162Detecting weak but hierarchically-structured patterns in networks[网络中弱层次结构模式的检测]
Aarti Singh(卡内基梅隆大学) The ability to detect weak distributed activation patterns in networks is critical to several applications, such as identifying the onset of anomalous...
热度：30
Aarti Singh(卡内基梅隆大学) The ability to detect weak distributed activation patterns in networks is critical to several applications, such as identifying the onset of anomalous...
热度：30
63Reduced-rank hidden Markov models [降秩隐马尔可夫模型]
Byron Boots(卡内基梅隆大学) Hsu et al.(2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their as...
热度：35
Byron Boots(卡内基梅隆大学) Hsu et al.(2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their as...
热度：35
64Coupled Semi-Supervised Learning for Information Extraction[用于信息抽取的耦合半监督学习]
Andrew Carlson(卡内基梅隆大学) We consider the problem of semi-supervised learning to extract categories (e.g., academic fields, athletes) and relations (e.g., PlaysSport (athlete, ...
热度：76
Andrew Carlson(卡内基梅隆大学) We consider the problem of semi-supervised learning to extract categories (e.g., academic fields, athletes) and relations (e.g., PlaysSport (athlete, ...
热度：76
65Collectively Representing Semi-Structured Data from the Web[从互联网中共同表示半结构化数据]
Bhavana Dalvi(卡内基梅隆大学) In this paper, we propose a single lowdimensional representation of a large collection of table and hyponym data, and show that with a small number of...
热度：22
Bhavana Dalvi(卡内基梅隆大学) In this paper, we propose a single lowdimensional representation of a large collection of table and hyponym data, and show that with a small number of...
热度：22
66Near-Bayesian Exploration in Polynomial Time[多项式时间内的近贝叶斯探测]
J. Zico Kolter(卡内基梅隆大学) We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to...
热度：29
J. Zico Kolter(卡内基梅隆大学) We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to...
热度：29
67What to Do When Search Fails: Finding Information by Association[搜索失败时该怎么办：按关联查找信息]
Duen Horng Chau(卡内基梅隆大学) Feldspar lets people find personal information on their computer by specifying chains of associated information as queries, emulating the retrieval pr...
热度：51
Duen Horng Chau(卡内基梅隆大学) Feldspar lets people find personal information on their computer by specifying chains of associated information as queries, emulating the retrieval pr...
热度：51
68Noise Thresholds for Spectral Clustering[噪声阀值的谱聚类算法]
Sivaraman Balakrishnan(卡内基梅隆大学) Although spectral clustering has enjoyed considerable empirical success in machine learning, its theoretical properties are not yet fully developed. W...
热度：89
Sivaraman Balakrishnan(卡内基梅隆大学) Although spectral clustering has enjoyed considerable empirical success in machine learning, its theoretical properties are not yet fully developed. W...
热度：89
69Adaptive Fourier-Domain Inference on the Symmetric Group[对称群的自适应傅立叶域推理]
Jonathan Huang(卡内基梅隆大学)
热度：39
Jonathan Huang(卡内基梅隆大学)
热度：39
70Student Travel Awards[学生旅游奖]
Kamal Nigam(卡内基梅隆大学) Andrew Arnold Sitaram Asur Meghana Deodhar Rong Ge Ming Hua Bo Long Ping Luo Qiaozhu Mei Flavia Moser Shady Shehata Victor Shengli Sheng ...
热度：45
Kamal Nigam(卡内基梅隆大学) Andrew Arnold Sitaram Asur Meghana Deodhar Rong Ge Ming Hua Bo Long Ping Luo Qiaozhu Mei Flavia Moser Shady Shehata Victor Shengli Sheng ...
热度：45