图 书 馆开课单位--莫纳什大学
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1Public water public space[公共水域公共空间]
Marko Fatur ;John Stanislav Sadar(莫纳什大学 ) Public water public space
热度：23
Marko Fatur ;John Stanislav Sadar(莫纳什大学 ) Public water public space
热度：23
2Difficulty-controllable Multi-hop Question Generation From Knowledge Graphs[从知识图生成可控多跳问题的难度]
Yuncheng Hua(莫纳什大学) Difficulty-controllable Multi-hop Question Generation From Knowledge Graphs
热度：36
Yuncheng Hua(莫纳什大学) Difficulty-controllable Multi-hop Question Generation From Knowledge Graphs
热度：36
3Robust Attribute and Structure Preserving Graph Embedding[鲁棒属性和结构保持图嵌入]
Bhagya Hettige(莫纳什大学) Robust Attribute and Structure Preserving Graph Embedding
热度：32
Bhagya Hettige(莫纳什大学) Robust Attribute and Structure Preserving Graph Embedding
热度：32
4Deep Cost-sensitive Kernel Machine for Binary Software Vulnerability Detection[用于二进制软件漏洞检测的深度成本敏感内核机器]
Tuan Nguyen(莫纳什大学) Deep Cost-sensitive Kernel Machine for Binary Software Vulnerability Detection
热度：44
Tuan Nguyen(莫纳什大学) Deep Cost-sensitive Kernel Machine for Binary Software Vulnerability Detection
热度：44
5Building Sparse Support Vector Machines for Multi-Instance Classification[建筑的稀疏支持向量机的多实例的分类]
Zhouyu Fu(莫纳什大学) We propose a direct approach to learning sparse Support Vector Machine (SVM) prediction models for Multi-Instance (MI) classification. The proposed sp...
热度：71
Zhouyu Fu(莫纳什大学) We propose a direct approach to learning sparse Support Vector Machine (SVM) prediction models for Multi-Instance (MI) classification. The proposed sp...
热度：71
6The Enhanced Crash Investigation Study (ECIS)[增强的事故调查研究（ECIS）]
Brian Fildes(莫纳什大学) The Enhanced Crash Investigation Study (ECIS) Background ECIS Project Objectives The Safe System Approach ECIS Method In-Depth Investig...
热度：37
Brian Fildes(莫纳什大学) The Enhanced Crash Investigation Study (ECIS) Background ECIS Project Objectives The Safe System Approach ECIS Method In-Depth Investig...
热度：37
7Resource -aware distributed online data mining for wireless sensor networks[资源分布-Aware在线数据挖掘的无线传感器网络]
Mohamed Medhat Gaber(莫纳什大学) Online data mining in wireless sensor networks is concerned with the problem of extracting knowledge from a large continuous amount of data streams wi...
热度：44
Mohamed Medhat Gaber(莫纳什大学) Online data mining in wireless sensor networks is concerned with the problem of extracting knowledge from a large continuous amount of data streams wi...
热度：44
8910A Model for Quality Guaranteed Resource-Aware Stream Mining[质量保证资源感知流挖掘模型]
Mohamed Medhat Gaber(莫纳什大学) Data streams are produced continuously at a high speed. Most data stream mining techniques address this challenge by using adaptation and approximatio...
热度：31
Mohamed Medhat Gaber(莫纳什大学) Data streams are produced continuously at a high speed. Most data stream mining techniques address this challenge by using adaptation and approximatio...
热度：31