检索结果-内蒙古大学图书馆

arXiv 2018年

作者： Xu, Kele Mi, Haibo Feng, Dawei Wang, Huaimin Chen, Chuan Zheng, Zibin Lan, Xu National Key Laboratory of Parallel and Distributed Processing Changsha China College of Computer National University of Defense Technology Changsha China School of Data and Computer Science Sun Yat-Sen University Guangzhou China Queen Mary University of London London United Kingdom

Valuable training data is often owned by independent organizations and located in multiple data centers. Most deep learning approaches require to centralize the multi-datacenter data for performance purpose. In practice, however, it is often infeasible to transfer all data to a centralized data center due to not only bandwidth limitation but also the constraints of privacy regulations. Model averaging is a conventional choice for data parallelized training, but its ineffectiveness is claimed by previous studies as deep neural networks are often non-convex. In this paper, we argue that model averaging can be effective in the decentralized environment by using two strategies, namely, the cyclical learning rate and the increased number of epochs for local model training. With the two strategies, we show that model averaging can provide competitive performance in the decentralized mode compared to the data-centralized one. In a practical environment with multiple data centers, we conduct extensive experiments using state-of-the-art deep network architectures on different types of data. Results demonstrate the effectiveness and robustness of the proposed method. Copyright © 2018, The Authors. All rights reserved.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

A Review of Indoor-Outdoor Scene Classification

A Review of Indoor-Outdoor Scene Classification

引用

2017 2nd International Conference on Control, Automation and Artificial Intelligence(CAAI2017)

作者： Zhehang Tong Dianxi Shi Bingzheng Yan Jing Wei National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology

ISBN: (纸本)9781510845541

Indoor-Outdoor scene classification problem have been proposed for almost 20 years and widely applied to general scene classification, image retrieval, image processing and robot application. But there is no consensus on one particular scene classification technique that can solve the Indoor-Outdoor scene classification problem perfectly. As larger image dataset has been developed and machine learning technology especially deep learning based methods achieve remarkable performance in computer vision, we aim to provide guidance and direction for researchers to tackle the Indoor-Outdoor scene classification problem with more powerful and robust solution through concluding the Indoor-Outdoor scene classification approaches which have been proposed in last 20 years. In this paper, we review the Indoor-Outdoor scene classification including feature extraction, classifier and related dataset. Their advantages and disadvantages are discussed. At last we conclude some challenging problems remain unsolved and propose some potential solutions.

关键词： indoor-outdoor scene classification computer vision

来源：评论

学校读者我要写书评

暂无评论

Exploring temporal preservation networks for precise temporal action localization

arXiv

引用

arXiv 2017年

作者： Yang, Ke Qiao, Peng Li, Dongsheng Lv, Shaohe Dou, Yong National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

Temporal action localization is an important task of computer vision. Though a variety of methods have been proposed, it still remains an open question how to predict the temporal boundaries of action segments precisely. Most works use segment-level classifiers to select video segments predetermined by action proposal or dense sliding windows. However, in order to achieve more precise action boundaries, a temporal localization system should make dense predictions at a fine granularity. A newly proposed work exploits Convolutional-Deconvolutional-Convolutional (CDC) filters to upsample the predictions of 3D ConvNets, making it possible to perform per-frame action predictions and achieving promising performance in terms of temporal action localization. However, CDC network loses temporal information partially due to the temporal downsampling operation. In this paper, we propose an elegant and powerful Temporal Preservation Convolutional (TPC) Network that equips 3D ConvNets with TPC filters. TPC network can fully preserve temporal resolution and downsample the spatial resolution simultaneously, enabling frame-level granularity action localization with minimal loss of time information. TPC network can be trained in an end-to-end manner. Experiment results on public datasets show that TPC network achieves significant improvement on per-frame action prediction and competing results on segment-level temporal action localization. Copyright © 2017, The Authors. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Cloudroid: A cloud framework for transparent and QoS-aware robotic computation outsourcing

arXiv

引用

arXiv 2017年

作者： Hu, Ben Wang, Huaimin Zhang, Pengfei Ding, Bo Che, Huimin National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology 410073 China

Many robotic tasks require heavy computation, which can easily exceed the robot's onboard computer capability. A promising solution to address this challenge is outsourcing the computation to the cloud. However, exploiting the potential of cloud resources in robotic software is difficult, because it involves complex code modification and extensive (re)configuration procedures. Moreover, quality of service (QoS) such as timeliness, which is critical to robot's behavior, have to be considered. In this paper, we propose a transparent and QoS-aware software framework called Cloudroid for cloud robotic applications. This framework supports direct deployment of existing robotic software packages to the cloud, transparently transforming them into Internet-accessible cloud services. And with the automatically generated service stubs, robotic applications can outsource their computation to the cloud without any code modification. Furthermore, the robot and the cloud can cooperate to maintain the specific QoS property such as request response time, even in a highly dynamic and resource-competitive environment. We evaluated Cloudroid based on a group of typical robotic scenarios and a set of software packages widely adopted in real-world robot practices. Results show that robots capability can be enhanced significantly without code modification and specific QoS objectives can be guaranteed. In certain tasks, the"cloud + robot" setup shows improved performance in orders of magnitude compared with the robot native setup. Copyright © 2017, The Authors. All rights reserved.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

Predicting potential gene ontology from cellular response data 17

Predicting potential gene ontology from cellular response da...

引用

5th International Conference on Bioinformatics and Computational Biology, ICBCB 2017

作者： Hong, Hao Yin, Xiaoyao Li, Fei Guan, Naiyang Bo, Xiaochen Luo, Zhigang Department of Chemistry and Biology National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Department of Biotechnology Beijing Institute of Radiation Medicine Beijing China

ISBN: (纸本)9781450348270

Ontologies have proven to be useful for capturing and organizing knowledge as a hierarchical set of terms and their relationships. However, curating gene ontology data by hand requires specialized knowledge of certain field, which is inefficient. Thus inferring gene ontology from the exponentially increased biological data is getting hot. Based on the Library of Integrated Network-Based Cellular Signatures (LINCS) data we came up with the hypothesis that genes participate in analogous biological processes might affect cells accordantly. By assessing cellular response after genes were knock out we built a similarity matrix with the Gene Set Enrichment Analysis (GSEA) and clustered the genes with affinity propagation algorithm. Next we mapped the cluster result to gene ontology biological process data for annotation and enrichment analysis, which confirmed our hypothesis and made it possible to predict biological processes for unannotated genes from cellular response data after genes are knock out for the first time. We further validated the rationality from the gene ontology molecular function data. © 2017 ACM.

关键词： Gene Ontology

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to “A distributed Relation Detection Approach in the Internet of Things”

引用

Mobile Information Systems 2019年第1期2019卷

作者： Weiping Zhu Hongliang Lu Xiaohui Cui Jiannong Cao International School of Software Wuhan University Wuhan *** Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha *** Department of Computing Hong Kong Polytechnic University Kowloon Hong Kongpolyu.edu.hk

来源：评论

学校读者我要写书评

暂无评论

HDSVM: A High Efficiency distributed SVM Framework over Data Stream

HDSVM: A High Efficiency Distributed SVM Framework over Data...

引用

IEEE International Symposium on parallel and distributed processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Yan Hou Yijie Wang Xingkong Ma Li Cheng College of Computer National University of Defense Technology Changsha National Laboratory for Parallel and Distributed Processing China

ISBN: (纸本)9781538637913

The application of Support Vector Machine (SVM) over data stream is growing with the increasing real-time processing requirements in classification field, like anomaly detection and real-time image processing. However, the dynamic live data with high volume and fast arrival rate in data streams make it challenging to apply SVM in data stream processing. Existing SVM implementations are mostly designed for batch processing and hardly satisfy the efficiency requirement of stream processing for its inherent complexity. To address the challenges, we propose a high efficiency distributed SVM framework over data stream (HDSVM), which consists of two main algorithms, incremental learning algorithm and distributed algorithm. Firstly, we propose a partial support vectors reserving incremental learning algorithm (PSVIL). By selecting a subset of support vectors based on their distances to classification hyperplane instead of the universal set to update SVM, the algorithm achieves lower time overhead while ensuring accuracy. Secondly, we propose a distribution remaining partition and fast aggregation distributed algorithm (DRPFA) for SVM. The real-time data is partitioned based on the original distribution with clustering instead of random partition, and historical support vectors are partitioned based on their distances to the classification hyperplane. The global hyperplane can be obtained by averaging the parameters of local hyperplanes due to the above partition strategy. Extensive experiments on Apache Storm show that the proposed HDSVM achieve lower time overhead and similar accuracy compared with the state-of-art. Speed-up ratio is increased by 2-8 times within 1% accuracy deviation.

关键词： Support vector machines Training distributed databases distributed algorithms Real-time systems Partitioning algorithms Streaming media

来源：评论

学校读者我要写书评

暂无评论

Mechanism of floating body effect mitigation via cutting off source injection in a fully-depleted silicon-on-insulator technology

引用

Chinese Physics B 2016年第3期25卷 283-289页

作者：黄鹏程陈书明陈建军 College of Computer National University of Defense Technology Changsha 410073 China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

In this paper, the effect of floating body effect （FBE） on a single event transient generation mechanism in fully depleted （FD） silicon-on-insulator （SOI） technology is investigated using three-dimensional technology computer-aided design （3D- TCAD） numerical simulation. The results indicate that the main SET generation mechanism is not carder drift/diffusion but floating body effect （FBE） whether for positive or negative channel metal oxide semiconductor （PMOS or NMOS）. Two stacking layout designs mitigating FBE are investigated as well, and the results indicate that the in-line stacking （IS） layout can mitigate FBE completely and is area penalty saving compared with the conventional stacking layout.

关键词： floating body effect in-line stacking silicon-on-insulator source injection

来源：评论

学校读者我要写书评

暂无评论

Crowd intelligence in AI 2.0 era

引用

Frontiers of Information Technology & Electronic Engineering 2017年第1期18卷 15-43页

作者： Wei LI Wen-jun WU Huai-min WANG Xue-qi CHENG Hua-jun CHEN Zhi-hua ZHOU Rong DING State Key Laboratory of Software Development Beihang University National Laboratory for Parallel and Distributed Processing College of ComputerNational University of Defense Technology Institute of Computing Technology Chinese Academy of Sciences College of Computer Science and Technology Zhejiang University National Key Laboratory for Novel Software Technology Nanjing University

The Internet based cyber-physical world has profoundly changed the information environment for the development of artificial intelligence(AI), bringing a new wave of AI research and promoting it into the new era of AI 2.0. As one of the most prominent characteristics of research in AI 2.0 era, crowd intelligence has attracted much attention from both industry and research communities. Specifically, crowd intelligence provides a novel problem-solving paradigm through gathering the intelligence of crowds to address challenges. In particular, due to the rapid development of the sharing economy, crowd intelligence not only becomes a new approach to solving scientific challenges, but has also been integrated into all kinds of application scenarios in daily life, e.g., online-tooffline(O2O) application, real-time traffic monitoring, and logistics management. In this paper, we survey existing studies of crowd intelligence. First, we describe the concept of crowd intelligence, and explain its relationship to the existing related concepts, e.g., crowdsourcing and human computation. Then, we introduce four categories of representative crowd intelligence platforms. We summarize three core research problems and the state-of-the-art techniques of crowd intelligence. Finally, we discuss promising future research directions of crowd intelligence.

关键词： Crowd intelligence Artificial intelligence 2.0 Crowdsourcing Human computation

来源：评论

学校读者我要写书评

暂无评论

Fine-grained checkpoint based on non-volatile memory

引用

Frontiers of Information Technology & Electronic Engineering 2017年第2期18卷 220-234页

作者： Wen-zhe ZHANG Kai LU Mikel LUJAN Xiao-ping WANG Xu ZHOU Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha 410072 China School of Computer The University of Manchester Manchester M13 9PL UK

New non-volatile memory （e.g., phase-change memory） provides fast access, large capacity, byteaddressability, and non-volatility features. These features, fast-byte-persistency, will bring new opportunities to fault tolerance. We propose a fine-grained checkpoint based on non-volatile memory. We extend the current virtual memory manager to manage non-volatile memory, and design a persistent heap with support for fast allocation and checkpointing of persistent objects. To achieve a fine-grained checkpoint, we scatter objects across virtual pages and rely on hardware page-protection to monitor the modifications. In our system, two objects in different virtual pages may reside on the same physical page. Modifying one object would not interfere with the other object. This allows us to monitor and checkpoint objects smaller than 4096 bytes in a fine-grained way. Compared with previous page-grained based checkpoint mechanisms, our new checkpoint method can greatly reduce the data copied at checkpoint time and better leverage the limited bandwidth of non-volatile memory.

关键词： Non-volatile memory Byte-persistency Persistent heap Fine-grained checkpoint

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：