开课单位--卡内基梅隆大学
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Joint Mining of Biological Text and Images: Case Studies[生物文本和图像的联合挖掘:案例研究]
Robert Murphy(卡内基梅隆大学) Categories Top » Computer Science » Text Mining Top » Computer Science » Bioinformatics Top » Computer Science »...
热度:57
Robert Murphy(卡内基梅隆大学) Categories Top » Computer Science » Text Mining Top » Computer Science » Bioinformatics Top » Computer Science »...
热度:57
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Image Analysis[图像分析]
Christos Faloutsos(卡内基梅隆大学) Categories Top » Computer Science » Image Analysis
热度:54
Christos Faloutsos(卡内基梅隆大学) Categories Top » Computer Science » Image Analysis
热度:54
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In-Use 4: A Mixed Initiative Semantic Web Framework for Process Composition[使用中的4:混合倡议语义Web框架Process组成]
Jinghai Rao(卡内基梅隆大学) author: Jinghai Rao, School of Computer Science, Carnegie Mellon University published: Feb. 25, 2007, recorded: November 2006,  ...
热度:40
Jinghai Rao(卡内基梅隆大学) author: Jinghai Rao, School of Computer Science, Carnegie Mellon University published: Feb. 25, 2007, recorded: November 2006,  ...
热度:40
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Splash Belief Propagation: Efficient Parallelization Through Asynchronous Scheduling[飞溅的信念传播:通过异步调度的并行效率]
Joseph Gonzalez(卡内基梅隆大学) In this work we focus on approximate parallel inference in loopy graphical models using loopy belief propagation. We demonstrate that the natural, ful...
热度:61
Joseph Gonzalez(卡内基梅隆大学) In this work we focus on approximate parallel inference in loopy graphical models using loopy belief propagation. We demonstrate that the natural, ful...
热度:61
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Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning [Priors样本大小的可识别性以及转移学习的应用]
Steve Hanneke(卡内基梅隆大学) We explore a transfer learning setting, in which a finite sequence of target concepts are sampled independently with an unknown distribution from a kn...
热度:46
Steve Hanneke(卡内基梅隆大学) We explore a transfer learning setting, in which a finite sequence of target concepts are sampled independently with an unknown distribution from a kn...
热度:46
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Feature Selection via Block-Regularized Regression[通过块正则化回归选择特征]
Seyoung Kim(卡内基梅隆大学) Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of line...
热度:74
Seyoung Kim(卡内基梅隆大学) Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of line...
热度:74
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Weighted Graphs and Disconnected Components: Patterns and a Generator[加权图和断开的组件:模式和生成器]
Mary McGlohon(卡内基梅隆大学) The vast majority of earlier work has focused on graphs which are both connected (typically by ignoring all but the giant connected component), and un...
热度:55
Mary McGlohon(卡内基梅隆大学) The vast majority of earlier work has focused on graphs which are both connected (typically by ignoring all but the giant connected component), and un...
热度:55
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Learning Patterns of the Brain: Machine Learning Challenges of fMRI Analysis[大脑的学习模式:功能磁共振成像分析的机器学习挑战]
Mark Palatucci(卡内基梅隆大学) Functional Magnetic Resonance Imaging (fMRI) has given neuroscientists and cognitive psychologists incredible power to analyze the deep mysteries of t...
热度:142
Mark Palatucci(卡内基梅隆大学) Functional Magnetic Resonance Imaging (fMRI) has given neuroscientists and cognitive psychologists incredible power to analyze the deep mysteries of t...
热度:142
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Structured Prediction: Maximum Margin Techniques[结构化预测:最大边际技术]
Nathan Ratliff(卡内基梅隆大学) Traditionally there has been a mismatch between the requirements of nontrivial applications and the prediction tools offered by machine learning. Appl...
热度:124
Nathan Ratliff(卡内基梅隆大学) Traditionally there has been a mismatch between the requirements of nontrivial applications and the prediction tools offered by machine learning. Appl...
热度:124
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A Globally Optimal Data-Driven Approach for Image Distortion Estimation[一个全局最优的图像失真估计的数据驱动的方法]
Yuandong Tian(卡内基梅隆大学) Image alignment in the presence of non-rigid distortions is a challenging task. Typically, this involves estimating the parameters of a dense deformat...
热度:30
Yuandong Tian(卡内基梅隆大学) Image alignment in the presence of non-rigid distortions is a challenging task. Typically, this involves estimating the parameters of a dense deformat...
热度:30