the proceedings contain 28 papers. the topics discussed include: passivity-based finite-time consensus for nonlinear fractional-order multi-agent systems;accelerating GNN inference by soft channel pruning;a multi-obje...
ISBN:
(纸本)9781665452182
the proceedings contain 28 papers. the topics discussed include: passivity-based finite-time consensus for nonlinear fractional-order multi-agent systems;accelerating GNN inference by soft channel pruning;a multi-object detection sampling algorithm for large scenes;comparative study on data sovereignty guarantee technology;cluster-based federated learning framework for intrusion detection;graph-based multi-view partial multi-label learning;hypergraphs: concepts, applications and analysis;traffic speed prediction of road cluster with heterogeneous sampling frequency;multi-selection attention for multimodal aspect-level sentiment classification;deep just-in-time consistent comment update via source code changes;do not have enough data? an easy data augmentation for code summarization;leveraging graph to improve lexicon enhanced Chinese sequence labelling;and parallel accelerating ultra-long read alignment by vertical partitioning data.
the alignment between sequencing reads and genome is a basic work in biological big data analysis. Each read of the third generation sequencing data is getting longer, and the data size is getting larger. To effective...
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Complex networks are a mainstream tool for understanding and modeling complex systems. Hypergraphs have been extensively studied in many fields due to its strong ability to represent higher-order group relationships a...
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ISBN:
(纸本)9781665452199
Complex networks are a mainstream tool for understanding and modeling complex systems. Hypergraphs have been extensively studied in many fields due to its strong ability to represent higher-order group relationships among objects. In this paper, we give a comprehensive overview of hypergraphs. We first introduce the background of hypergraph and some basic terminologies. then, we review hypergraph generation methods and representation methods combined with some downstream tasks, such as vertex classification, hyperedge prediction. Finally, we look into topological properties of some typical hypergraphs, including vertex degree distribution, hyperedge degree distribution, connectivity, etc. the paper concludes with a discussion of application and promising future directions of hypergraphs.
this paper tackles the output consensus problem for second-order nonlinear multi-agent systems (SNMASs). By virtue of the devised output feedback controller, an output consensus criterion is put forward for the SNMAS....
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ISBN:
(纸本)9781665452199
this paper tackles the output consensus problem for second-order nonlinear multi-agent systems (SNMASs). By virtue of the devised output feedback controller, an output consensus criterion is put forward for the SNMAS. Moreover, an adaptive output feedback control scheme is also developed to guarantee that SNMAS can achieve the output consensus. Finally, the proposed control protocols are verified through a numerical example.
We propose a MIP programming model for the bird’s nest detection on the railway catenary, which performs coarse-to-fine strategy based on a cascaded YOLO network, and calculates the coarse-level and fine-level detect...
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ISBN:
(纸本)9781665452199
We propose a MIP programming model for the bird’s nest detection on the railway catenary, which performs coarse-to-fine strategy based on a cascaded YOLO network, and calculates the coarse-level and fine-level detection in parallel for different detected images. Due to the optimization of the parallel pipeline acceleration model, the deep learning network has a running speed equivalent to that of the single-stage network, which can perform real-time detection of bird’s nest.
An exponential increase in the speed of DNA sequencing over the past decade has driven demand for fast, space-efficient algorithms to process the resultant data. the first step in processing is alignment of many short...
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ISBN:
(纸本)9781479959198
An exponential increase in the speed of DNA sequencing over the past decade has driven demand for fast, space-efficient algorithms to process the resultant data. the first step in processing is alignment of many short DNA sequences, or reads, against a large reference sequence. this work presents WOODSTOCC, an implementation of short-read alignment designed for Graphics Processing Unit (GPU) architectures. WOODSTOCC translates a novel CPU implementation of gapped short-read alignment, which has guaranteed optimal and complete results, to the GPU. Our implementation combines an irregular trie search with dynamic programming to expose regularly structured parallelism. We first describe this implementation, then discuss its port to the GPU. WOODSTOCC's GPU port exploits three generally useful techniques for extracting regular parallelism from irregular computations: dynamic thread mapping with a worklist, kernel stage decoupling, and kernel slicing. We discuss the performance impact of these techniques and suggest further opportunities for improvement.
Recently BERT has been employed for encoding a sequence of input characters in state-of-the-art Chinese sequence labelling models. However, Chinese sequence labelling often faces the lack of explicit word boundaries, ...
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ISBN:
(纸本)9781665452199
Recently BERT has been employed for encoding a sequence of input characters in state-of-the-art Chinese sequence labelling models. However, Chinese sequence labelling often faces the lack of explicit word boundaries, which is well-noticed and more challenging problem. To alleviate this problem, we adopt the containing relation between characters and self-matched words from external lexicon to construct graph and incorporate lexicon-based graph information into the lower layers of BERT. We evaluate our model on ten Chinese datasets of three classic tasks containing Named Entity Recognition, Word Segmentation and Part-of-Speech Tagging. the experimental results demonstrate the effectiveness of our proposed method.
We propose a novel multi-view spectral clustering model, called Joint Original space and Latent space for Multi-view clustering (JOLM). Different from most existing multi-view clustering methods, which usually improve...
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ISBN:
(纸本)9781665452199
We propose a novel multi-view spectral clustering model, called Joint Original space and Latent space for Multi-view clustering (JOLM). Different from most existing multi-view clustering methods, which usually improve clustering performance by developing original or latent features of multi-view data, the proposed JOLM method integrates both original features and latent features into a framework to improve clustering performance. Specifically, we learn the similarity graph matrix from original multiple features and latent features respectively, and obtain the global graph by minimizing the errors between them, so as to better utilize the rich information from multiple views. An effective iterative algorithm is proposed to optimize the objective function. Finally, abundant experiments show the effectiveness of our proposed method.
the construction of heterogeneous social networks enables the major social platforms in the network to connect through social information. In order to ensure network security and improve downstream tasks such as user ...
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ISBN:
(纸本)9781665452199
the construction of heterogeneous social networks enables the major social platforms in the network to connect through social information. In order to ensure network security and improve downstream tasks such as user profile, knowledge graph construction and recommendation, the relevance measurement between social information has attracted extensive attention in recent years. Although HeteSim algorithm has achieved good results in measuring the relevance between heterogeneous nodes, this method only focuses on the structure features between nodes, and fails to comprehensively consider the joint impact of structure features and semantic features. therefore, this paper proposes HeteSim-Measured algorithm that considers the fusion of structure features and semantic features for improving the accuracy of relevance measurement. the experiment is verified by measuring the relevance based on meta-path on the datasets and comparing with HeteSim algorithm.
As an economic commodity, data sharing, circulation and trading can not only reduce the maintenance and management costs of enterprises, but also tap the potential value of data, improve the internal workflow of enter...
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ISBN:
(纸本)9781665452199
As an economic commodity, data sharing, circulation and trading can not only reduce the maintenance and management costs of enterprises, but also tap the potential value of data, improve the internal workflow of enterprises and the cooperation among enterprises. the marketization of data elements and the clarification of data sovereignty are the current difficulties hindering data flow. this paper addresses one of the current data circulation issues: how to maintain data sovereignty, and makes exploration and research in combination withthe current era background. For the current research projects and products, compare and analyze the techniques used to maintain data sovereignty. Finally, based on the current technology, it gives recommendations for the future development of data sovereignty protection technology.
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