开课单位--卡内基梅隆大学
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Detecting 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:32
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:32
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Reduced-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:37
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:37
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Coupled 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:83
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:83
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Collectively 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:27
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:27
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Near-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:34
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:34
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What 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:56
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:56
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Noise 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:93
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:93
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Adaptive 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:43
Jonathan Huang(卡内基梅隆大学)
热度:43
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Student 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:46
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:46