图 书 馆开课单位--卡内基梅隆大学
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121Exploiting document structure and feature hierarchy for semi-supervised domain adaptation[开发半监督领域适应的文档结构和特征层次]
Andrew Arnold(卡内基梅隆大学) In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target d...
热度：77
Andrew Arnold(卡内基梅隆大学) In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target d...
热度：77
122From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series[从推文到民意调查：将文本情感与民意时间序列联系起来]
Brendan O'Connor(卡内基梅隆大学) We connect measures of public opinion measured from polls with sentiment measured from text. We analyze several surveys on consumer confidence and pol...
热度：51
Brendan O'Connor(卡内基梅隆大学) We connect measures of public opinion measured from polls with sentiment measured from text. We analyze several surveys on consumer confidence and pol...
热度：51
123Turning Down the Noise in the Blogosphere [降低博客圈中的噪声]
Gaurav Veda(卡内基梅隆大学) In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information...
热度：56
Gaurav Veda(卡内基梅隆大学) In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information...
热度：56
124Machine Learning in the Cloud with GraphLab[机器学习在云graphlab]
Carlos Guestrin(卡内基梅隆大学) Exponentially increasing dataset sizes have driven Machine Learning experts to explore using parallel and distributed computing for their research. Fu...
热度：94
Carlos Guestrin(卡内基梅隆大学) Exponentially increasing dataset sizes have driven Machine Learning experts to explore using parallel and distributed computing for their research. Fu...
热度：94
125Probability Distributions on Permutations: Compact Representations and Inference[排列的概率分布：紧凑的表示和推理]
Jonathan Huang(卡内基梅隆大学) Permutations arise in a variety of real-world problems, such as voting, ranking, and data association. Representing uncertainty over permutations, how...
热度：182
Jonathan Huang(卡内基梅隆大学) Permutations arise in a variety of real-world problems, such as voting, ranking, and data association. Representing uncertainty over permutations, how...
热度：182
126CORL: A Continuous-state Offset-dynamics Reinforcement Learner[CORL：一个连续状态偏移动力学强化学习]
Emma Brunskill(卡内基梅隆大学) Continuous state spaces and stochastic, switching dynamics characterize a number of rich, real world domains, such as robot navigation across varying ...
热度：48
Emma Brunskill(卡内基梅隆大学) Continuous state spaces and stochastic, switching dynamics characterize a number of rich, real world domains, such as robot navigation across varying ...
热度：48
127128Spectral Graph Theory, Linear Solvers and Applications [谱图理论，线性求解器及其应用]
Gary L Miller(卡内基梅隆大学) We discuss the development of combinatorial methods for solving symmetric diagonally dominate linear systems. Over the last fifteen years the computer...
热度：50
Gary L Miller(卡内基梅隆大学) We discuss the development of combinatorial methods for solving symmetric diagonally dominate linear systems. Over the last fifteen years the computer...
热度：50
129Structured Correspondence Topic Models for Mining Captioned Figures in Biological Literature[结构对应的主题模式挖掘在生物文献标题数据]
Amr Ahmed(卡内基梅隆大学) .主要的信息来源（通常是最重要的信息的一部分）在科学期刊的学术文章，诉讼和图书的数字，直接提供的图像和关键的实验结果和科学内容的其他图形插图。在生物制...
热度：31
Amr Ahmed(卡内基梅隆大学) .主要的信息来源（通常是最重要的信息的一部分）在科学期刊的学术文章，诉讼和图书的数字，直接提供的图像和关键的实验结果和科学内容的其他图形插图。在生物制...
热度：31
130Activized Learning: Transforming Passive to Active with Improved Label Complexity [活跃的学习：改变被动为主动改进标签的复杂性]
Steve Hanneke(卡内基梅隆大学) In active learning, a learning algorithm is given access to a large pool of unlabeled examples, and is allowed to request the labels of any particular...
热度：36
Steve Hanneke(卡内基梅隆大学) In active learning, a learning algorithm is given access to a large pool of unlabeled examples, and is allowed to request the labels of any particular...
热度：36