图 书 馆开课单位--俄勒冈州立大学
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1Cost-Sensitive Top-Down/Bottom-Up Inference for Multiscale Activity Recognition[多尺度活动识别的成本敏感自顶向下/自下而上推理]
Mohamed Amer(俄勒冈州立大学) This paper addresses a new problem, that of multiscale activity recognition. Our goal is to detect and localize a wide range of activities, including ...
热度：66
Mohamed Amer(俄勒冈州立大学) This paper addresses a new problem, that of multiscale activity recognition. Our goal is to detect and localize a wide range of activities, including ...
热度：66
2Challenges for Machine Learning in Computational Sustainability[计算机可持续发展中机器学习面临的挑战]
Thomas Dietterich(俄勒冈州立大学) Research in computational sustainability seeks to develop and apply methods from computer science to the many challenges of managing the earth's e...
热度：35
Thomas Dietterich(俄勒冈州立大学) Research in computational sustainability seeks to develop and apply methods from computer science to the many challenges of managing the earth's e...
热度：35
3Iterative Learning of Weighted Rule Sets for Greedy Search[贪婪搜索加权规则集的迭代学习]
Yuehua Xu(俄勒冈州立大学) Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider le...
热度：61
Yuehua Xu(俄勒冈州立大学) Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider le...
热度：61
4Steps Toward Robust Artificial Intelligence[迈向强大的人工智能的步骤]
Thomas G. Dietterich(俄勒冈州立大学) Steps Toward Robust Artificial Intelligence
热度：37
Thomas G. Dietterich(俄勒冈州立大学) Steps Toward Robust Artificial Intelligence
热度：37
5Machine Learning in Ecosystem Informatics and Sustainability[在生态系统中的信息的机器学习和可持续性]
Thomas Dietterich, Carlos Guestrin(俄勒冈州立大学) Ecosystem Informatics brings together mathematical and computational tools to address scientific and policy challenges in the ecosystem sciences. Thes...
热度：61
Thomas Dietterich, Carlos Guestrin(俄勒冈州立大学) Ecosystem Informatics brings together mathematical and computational tools to address scientific and policy challenges in the ecosystem sciences. Thes...
热度：61
6Adapting the Right Measures for K-Means Clustering[K均值聚类调整合适的措施]
Junjie Wu(俄勒冈州立大学) Clustering validation is a long standing challenge in the clustering literature. While many validation measures have been developed for evaluating the...
热度：62
Junjie Wu(俄勒冈州立大学) Clustering validation is a long standing challenge in the clustering literature. While many validation measures have been developed for evaluating the...
热度：62
7Cost-Sensitive Top-Down/Bottom-Up Inference for Multiscale Activity Recognition[成本敏感的自上而下的/底部的多尺度行为识别推理]
Ivan Laptev, Michael J. Black, Mohamed Amer(俄勒冈州立大学) This paper addresses a new problem, that of multiscale activity recognition. Our goal is to detect and localize a wide range of activities, including ...
热度：95
Ivan Laptev, Michael J. Black, Mohamed Amer(俄勒冈州立大学) This paper addresses a new problem, that of multiscale activity recognition. Our goal is to detect and localize a wide range of activities, including ...
热度：95
8ILP Invited Panel - Structured Machine Learning: The Next 10 Years[ILP邀请小组结构化机器学习：未来10年]
Thomas Dietterich, Stephen Muggleton, Bernhard Pfahringer, Lise Getoor, Pedro Domingos(俄勒冈州立大学) ILP Invited Panel - Structured Machine Learning: The Next 10 Years.
热度：46
Thomas Dietterich, Stephen Muggleton, Bernhard Pfahringer, Lise Getoor, Pedro Domingos(俄勒冈州立大学) ILP Invited Panel - Structured Machine Learning: The Next 10 Years.
热度：46
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