图 书 馆开课单位--西蒙弗雷泽大学
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1Motion planning of multiple agents in virtual environments[虚拟环境中多智能体的运动规划]
Kamal Gupta;Yi Li(西蒙弗雷泽大学) Describes and demonstrates in simulation the use of coordination graphs to avoid collisions of multiple agents in tasks requiring motion of multiple a...
热度：24
Kamal Gupta;Yi Li(西蒙弗雷泽大学) Describes and demonstrates in simulation the use of coordination graphs to avoid collisions of multiple agents in tasks requiring motion of multiple a...
热度：24
2Joint Cluster Analysis of Attribute and Relationship Data Without Priori Specification of the Number of Clusters [属性和关系数据的联合聚类分析没有群集数的先验的规范]
Flavia Moser(西蒙弗雷泽大学) 在许多应用中，属性和关系的数据是可用的，携带的互补信息的真实世界的实体。在这种情况下，一个联合分析两种类型的数据可以得到比经典的聚类算法，要么只使用属...
热度：46
Flavia Moser(西蒙弗雷泽大学) 在许多应用中，属性和关系的数据是可用的，携带的互补信息的真实世界的实体。在这种情况下，一个联合分析两种类型的数据可以得到比经典的聚类算法，要么只使用属...
热度：46
3Boosting with Incomplete Information[不完全信息的提高]
Yang Wang(西蒙弗雷泽大学) In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corr...
热度：41
Yang Wang(西蒙弗雷泽大学) In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corr...
热度：41
4Neighbor Query Friendly Compression of Social Networks[社交网络的邻居查询友好压缩]
Hossein Maserrat(西蒙弗雷泽大学) Compressing social networks can substantially facilitate mining and advanced analysis of large social networks. Preferably, social networks should be ...
热度：50
Hossein Maserrat(西蒙弗雷泽大学) Compressing social networks can substantially facilitate mining and advanced analysis of large social networks. Preferably, social networks should be ...
热度：50
5A Multi-Relational Approach to Spatial Classification[一种空间分类的多关系方法]
Richard Frank(西蒙弗雷泽大学) Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships t...
热度：41
Richard Frank(西蒙弗雷泽大学) Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships t...
热度：41
6Specularity and Shadow Interpolation via Robust Polynomial Texture Maps[通过强大的高光和阴影插值多项式纹理]
Nasim Hajari(西蒙弗雷泽大学) 通过强大的高光和阴影插值多项式纹理
热度：31
Nasim Hajari(西蒙弗雷泽大学) 通过强大的高光和阴影插值多项式纹理
热度：31
7Cleaning Disguised Missing Data: A Heuristic Approach [清洗伪装丢失数据：一种启发式方法 ]
Jian Pei(西蒙弗雷泽大学) In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but ins...
热度：51
Jian Pei(西蒙弗雷泽大学) In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but ins...
热度：51
8Mining Uncertain and Probabilistic Data: problems, Challenges, Methods, and Applications[挖掘不确定和概率数据：问题、挑战、方法和应用]
Jian Pei, Ming Hua(西蒙弗雷泽大学 ) Uncertain data are inherent in some important applications, such as environmental surveillance, market analysis, and quantitative economics research. ...
热度：37
Jian Pei, Ming Hua(西蒙弗雷泽大学 ) Uncertain data are inherent in some important applications, such as environmental surveillance, market analysis, and quantitative economics research. ...
热度：37
9Constraint-Driven Clustering [约束驱动的聚类]
Rong Ge(西蒙弗雷泽大学) Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while ne...
热度：39
Rong Ge(西蒙弗雷泽大学) Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while ne...
热度：39
10Saliency-Cognizant Error Concealment In Loss-Corrupted Streaming Video[丢失损坏的流媒体视频中的显着性 - 认知错误隐藏]
Hadi Hadizadeh(西蒙弗雷泽大学) Error concealment in packet-loss-corrupted streaming video is inherently an under-determined problem, as there are insufficient number of well-defined...
热度：40
Hadi Hadizadeh(西蒙弗雷泽大学) Error concealment in packet-loss-corrupted streaming video is inherently an under-determined problem, as there are insufficient number of well-defined...
热度：40
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