图 书 馆开课单位--卡内基梅隆大学
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81Joint 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：55
Robert Murphy(卡内基梅隆大学) Categories Top » Computer Science » Text Mining Top » Computer Science » Bioinformatics Top » Computer Science »...
热度：55
82Image Analysis[图像分析]
Christos Faloutsos(卡内基梅隆大学) Categories Top » Computer Science » Image Analysis
热度：50
Christos Faloutsos(卡内基梅隆大学) Categories Top » Computer Science » Image Analysis
热度：50
83In-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：36
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：36
84Splash 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：59
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：59
85Identifiability 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：43
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：43
86Feature 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：70
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：70
87Weighted 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
88Learning 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：140
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：140
89Structured 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：112
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：112
90A 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：29
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：29