图 书 馆开课单位--卡内基梅隆大学
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51Pose Machines: Articulated Pose Estimation via Inference Machines[姿态机：通过推理机进行关节姿态估计]
Varun Ramakrishna(卡内基梅隆大学) State-of-the-art approaches for articulated human pose estimation are rooted in parts-based graphical models. These models are often restricted to tre...
热度：42
Varun Ramakrishna(卡内基梅隆大学) State-of-the-art approaches for articulated human pose estimation are rooted in parts-based graphical models. These models are often restricted to tre...
热度：42
52Mining Billion-node Graphs: Patterns, Generators and Tools[挖掘亿节点图：模式，发电机和工具]
Christos Faloutsos(卡内基梅隆大学) What do graphs look like? How do they evolve over time? How to handle a graph with a billion nodes? We present a comprehensive list of static and temp...
热度：62
Christos Faloutsos(卡内基梅隆大学) What do graphs look like? How do they evolve over time? How to handle a graph with a billion nodes? We present a comprehensive list of static and temp...
热度：62
53REGO: Rank-based estimation of Renyi information using Euclidean graph optimization[REGO：基于欧氏图优化的Renyi信息秩估计]
Barnabás Póczos(卡内基梅隆大学) We propose a new method for a non-parametric estimation of Renyi and Shannon information for a multivariate distribution using a corresponding copula,...
热度：32
Barnabás Póczos(卡内基梅隆大学) We propose a new method for a non-parametric estimation of Renyi and Shannon information for a multivariate distribution using a corresponding copula,...
热度：32
54Interview with Tom Mitchell[汤姆米切尔访谈]
Tom Mitchell, Davor Orlič(卡内基梅隆大学) **Tom Mitchell is the first Chair of Department of the first Machine Learning Department in the World**, based at Carnegie Mellon. The Videolectures.N...
热度：52
Tom Mitchell, Davor Orlič(卡内基梅隆大学) **Tom Mitchell is the first Chair of Department of the first Machine Learning Department in the World**, based at Carnegie Mellon. The Videolectures.N...
热度：52
55Domain Adaptation for Mobile Robot Navigation[移动机器人导航域适配 ]
David Bradley(卡内基梅隆大学) An important challenge in outdoor mobile robotic perception is maintaining terrain classification performance throughout the extremely variable condit...
热度：67
David Bradley(卡内基梅隆大学) An important challenge in outdoor mobile robotic perception is maintaining terrain classification performance throughout the extremely variable condit...
热度：67
56Data-Driven Scene Understanding from 3D Models[3D模型中的数据驱动场景理解]
Scott Satkin(卡内基梅隆大学) In this paper, we propose a data-driven approach to leverage repositories of 3D models for scene understanding. Our ability to relate what we see in a...
热度：139
Scott Satkin(卡内基梅隆大学) In this paper, we propose a data-driven approach to leverage repositories of 3D models for scene understanding. Our ability to relate what we see in a...
热度：139
57The Web Changes Everything: Understanding the Dynamics of Web Content[互联网改变了一切：了解网页内容的动态性]
Susan T. Dumais;Jaime Teevan;Jonathan Elsas;Eytan Adar(卡内基梅隆大学) The Web Changes Everything: Understanding the Dynamics of Web Content
热度：26
Susan T. Dumais;Jaime Teevan;Jonathan Elsas;Eytan Adar(卡内基梅隆大学) The Web Changes Everything: Understanding the Dynamics of Web Content
热度：26
58Fast learning of Document Ranking Functions with the Committee Perceptron[快速学习委员会感知器的文档排序功能]
Jonathan Elsas(卡内基梅隆大学) Fast learning of Document Ranking Functions with the Committee Perceptron
热度：28
Jonathan Elsas(卡内基梅隆大学) Fast learning of Document Ranking Functions with the Committee Perceptron
热度：28
59Semi-Supervised Learning and Learning via Similarity Functions: two key settings for Data-dependent Concept Spaces[基于相似函数的半监督学习：数据相关概念空间的两种关键设置]
Avrim Blum(卡内基梅隆大学) Semi-Supervised Learning and Learning via Similarity Functions: two key settings for Data-dependent Concept Spaces
热度：77
Avrim Blum(卡内基梅隆大学) Semi-Supervised Learning and Learning via Similarity Functions: two key settings for Data-dependent Concept Spaces
热度：77
60A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning[减少模仿学习和结构化预测的没遗憾的在线学习]
Stephane Ross(卡内基梅隆大学) Sequential prediction problems such as imitation learning, where future observations depend on previous predictions (actions), violate the common i.i....
热度：82
Stephane Ross(卡内基梅隆大学) Sequential prediction problems such as imitation learning, where future observations depend on previous predictions (actions), violate the common i.i....
热度：82