开课单位--卡内基梅隆大学
71
72
73
74
75
76
77
78
79
80
![](functions/showpic.php?filename=2015122910101781.png)
Introduction to the Machine Learning over Text & Images - Autumn School by Eric Xing[对机器学习的文本介绍]
Eric P. Xing(卡内基梅隆大学)
热度:32
Eric P. Xing(卡内基梅隆大学)
热度:32
![](functions/showpic.php?filename=2015110903291986.jpg)
Adventures in Scheduling: Some Trends in Operations Research[冒险在调度:运筹学中的一些趋势]
Michael Trick(卡内基梅隆大学) Major League Baseball is a multi-billion dollar per year industry that relies heavily on the quality of its schedule. Teams, fans, TV networks, and ev...
热度:34
Michael Trick(卡内基梅隆大学) Major League Baseball is a multi-billion dollar per year industry that relies heavily on the quality of its schedule. Teams, fans, TV networks, and ev...
热度:34
![](functions/showpic.php?filename=2015110903271780.jpg)
Fast Direction-Aware Proximity for Graph Mining [快速方向图挖掘到接近]
Hanghang Tong(卡内基梅隆大学) 本文研究了不对称的邻近措施对有向图,其量化关系的两个或两组节点之间的节点。在几个图挖掘任务,包括聚类的措施是有用的,链接预测和连接的拓扑发现。我们的邻...
热度:81
Hanghang Tong(卡内基梅隆大学) 本文研究了不对称的邻近措施对有向图,其量化关系的两个或两组节点之间的节点。在几个图挖掘任务,包括聚类的措施是有用的,链接预测和连接的拓扑发现。我们的邻...
热度:81
![](functions/showpic.php?filename=2015110903125953.jpg)
DynaMMo: Mining and Summarization of Coevolving Sequences with Missing Values[dynammo:共同进化序列的缺失值的挖掘和总结]
Christos Faloutsos(卡内基梅隆大学) Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discove...
热度:48
Christos Faloutsos(卡内基梅隆大学) Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discove...
热度:48
![](functions/showpic.php?filename=2015112205202425.png)
Learning Feature Hierarchies by Learning Deep Generative Models[学习特征层次的学习深度生成模型]
Ruslan Salakhutdinov(卡内基梅隆大学) In this paper we present several ideas based on learning deep generative models from high-dimensional, richly structured sensory input. We will exploi...
热度:35
Ruslan Salakhutdinov(卡内基梅隆大学) In this paper we present several ideas based on learning deep generative models from high-dimensional, richly structured sensory input. We will exploi...
热度:35
![](functions/showpic.php?filename=2015122901471072.png)
Evaluating the inverse decision-making approach to preference learning[逆决策偏好的学习方法的评价]
Alan Jern(卡内基梅隆大学) Psychologists have recently begun to develop computational accounts of how people infer others' preferences from their behavior. The inverse decis...
热度:60
Alan Jern(卡内基梅隆大学) Psychologists have recently begun to develop computational accounts of how people infer others' preferences from their behavior. The inverse decis...
热度:60
![](functions/showpic.php?filename=2015122910082017.png)
![](functions/showpic.php?filename=2015122910113787.png)
Interview with Eric Xing[埃里克兴采访]
Eric P. Xing(卡内基梅隆大学) Statistical machine learning theory and applications in computational biology are the **fields of interest of Eric Xing**. We asked him at this interv...
热度:131
Eric P. Xing(卡内基梅隆大学) Statistical machine learning theory and applications in computational biology are the **fields of interest of Eric Xing**. We asked him at this interv...
热度:131
![](functions/showpic.php?filename=2015122910125143.png)
![](functions/showpic.php?filename=2015122910172383.png)