图 书 馆开课单位--宾夕法尼亚州立大学
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1IntelliLight: a Reinforcement Learning Approach for Intelligent Traffic Light Control[IntelliLight：一种用于智能交通灯控制的强化学习方法]
Guanjie Zheng(宾夕法尼亚州立大学) The intelligent traffic light control is critical for an efficient transportation system. While existing traffic lights are mostly operated by hand-cr...
热度：51
Guanjie Zheng(宾夕法尼亚州立大学) The intelligent traffic light control is critical for an efficient transportation system. While existing traffic lights are mostly operated by hand-cr...
热度：51
2Sequential Hypothesis Tests for Markov Models of Time-Series Data[时间序列数据马尔可夫模型的序列假设检验]
Nurali Virani(宾夕法尼亚州立大学) This paper presents new results on sequential hypothesis tests for Markov models of time series data. In particular, a technique for sequential hypoth...
热度：38
Nurali Virani(宾夕法尼亚州立大学) This paper presents new results on sequential hypothesis tests for Markov models of time series data. In particular, a technique for sequential hypoth...
热度：38
3SRVAR: Joint Discrete Hidden State Discovery and Structure Learning from Time Series Data[SRVAR：基于时间序列数据的联合离散隐状态发现和结构学习]
Tsung-Yu Hsieh(宾夕法尼亚州立大学) SRVAR: Joint Discrete Hidden State Discovery and Structure Learning from Time Series Data
热度：45
Tsung-Yu Hsieh(宾夕法尼亚州立大学) SRVAR: Joint Discrete Hidden State Discovery and Structure Learning from Time Series Data
热度：45
4MedPath: Augmenting Health Risk Prediction via Medical Knowledge Paths[MedPath：通过医学知识路径增强健康风险预测]
Muchao Ye(宾夕法尼亚州立大学) MedPath: Augmenting Health Risk Prediction via Medical Knowledge Paths
热度：89
Muchao Ye(宾夕法尼亚州立大学) MedPath: Augmenting Health Risk Prediction via Medical Knowledge Paths
热度：89
5UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data[UNITE：利用多源数据进行基于不确定性的健康风险预测]
Chacha Chen(宾夕法尼亚州立大学) UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data
热度：35
Chacha Chen(宾夕法尼亚州立大学) UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data
热度：35
6Mining Periodic Behaviors for Moving Objects[运动目标的周期行为挖掘]
Zhenhui Jessie Li(宾夕法尼亚州立大学) Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. Howeve...
热度：52
Zhenhui Jessie Li(宾夕法尼亚州立大学) Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. Howeve...
热度：52
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8Lessons for Cyber-infrastructure and Web[网络基础设施和网络课程]
Lee Giles(宾夕法尼亚州立大学) E-science or cyberinfrastructure have become crucial for scientific progress and open source systems have greatly facilitated design and implementatio...
热度：48
Lee Giles(宾夕法尼亚州立大学) E-science or cyberinfrastructure have become crucial for scientific progress and open source systems have greatly facilitated design and implementatio...
热度：48
9SIMCOMP: A Hybrid Soft Clustering of Metagenome Reads[simcomp：元基因组读取的混合软聚类 ]
Shruthi Prabhakara(宾夕法尼亚州立大学) A major challenge facing metagenomics is the development of tools for the characterization of functional and taxonomic content of vast amounts of shor...
热度：70
Shruthi Prabhakara(宾夕法尼亚州立大学) A major challenge facing metagenomics is the development of tools for the characterization of functional and taxonomic content of vast amounts of shor...
热度：70
10Mining Periodic Behaviors for Moving Objects[挖掘运动对象的周期行为]
Zhenhui Li(宾夕法尼亚州立大学 ) Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. Howeve...
热度：69
Zhenhui Li(宾夕法尼亚州立大学 ) Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. Howeve...
热度：69
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