Support Vector Machines (SVMs) are powerful classification tools. However, the model training is very time-consuming when meeting large scale data sets. Some efforts have been devoted to screening out non-support vect...
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ISBN:
(纸本)9781509044603
Support Vector Machines (SVMs) are powerful classification tools. However, the model training is very time-consuming when meeting large scale data sets. Some efforts have been devoted to screening out non-support vectors (non-SVs) to accelerate the training. But their processes rely on prior knowledge of other classifiers with different parameters to screen out non-SVs. In this paper, we propose Directional Indicator Support Vector Machines (DISVMs) to efficiently identify non-SVs. DISVMs employs a directional indicator, which points to the approximately orthogonal direction of the separating hyperplane, to qualitatively define the location of different samples and thus identify non-SVs. Furthermore, DISVMs leverages a two-stage algorithm: the first stage is to compute the directional indicator. The second stage is to identify non-SVs using the indicator. To avoid misjudgement, we propose CnSV method for non-SVs based on the majority rule. DISVMs screens out non-SVs with light computation and little accuracy loss. Experiments show that our approach significantly reduces the total computation cost.
As the big data era is coming,it brings new challenges to the massive data processing.A combination of GPU and CPU on chip is the trend to release the pressure of large scale *** found that there are different memory ...
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As the big data era is coming,it brings new challenges to the massive data processing.A combination of GPU and CPU on chip is the trend to release the pressure of large scale *** found that there are different memory access characteristics between GPU and *** most important one is that the programs of GPU include a large number of threads,which lead to higher access frequency in cache than the CPU *** the LRU policy favors the programs with high memory access frequency,the programs of GPU can't get the corresponding performance boost even more cache resources are *** LRU policy is not suitable for heterogeneous multi-core *** on the different characteristics of GPU and CPU programs on memory access,this paper proposes an LLC dynamic replacement policy--DIPP(Dynamic Insertion/Promotion Policy) for heterogeneous multi-core *** core idea of the replacement policy is to reduce the miss rate of the program and enhance the overall system performance by limiting the cache resources that GPU can acquire and reducing the thread interferences between *** compare the DIPP replacement policy with LRU and we conduct a classified discussion according to the program results of *** programs enhance 23.29% on the average performance(using arithmetic mean).Large working sets programs can improve 13.95%,compute-intensive programs enhance 9.66% and stream class programs improve 3.8%.
Compensating CSP (cCSP) models long-running transactions. It can be used to specify service orchestrations written in programming languages like WS-BPEL. However, the original cCSP does not allow to model internal (no...
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Public auditing is a new technique to protect the integrity of outsourced data in the remote cloud. Users delegate the ability of auditing to a third party auditor (TPA), and assume that each result from the TPA is co...
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With the development of high performance computing and Web 2.0 applications,unstructured data storage becomes more and more *** RDBMS isn't efficient for big data ***,RDBMS's scalability is ***' expansion ...
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With the development of high performance computing and Web 2.0 applications,unstructured data storage becomes more and more *** RDBMS isn't efficient for big data ***,RDBMS's scalability is ***' expansion often leads to a large scale of data *** paper designs and implements a high performance distributed key-value database,which is distributed Stage *** servers are organized by a consistent hashing ring and distributed with the support of Zookeeper,a distributed service *** has a high single-node read/write *** route information is calculated by clients,which reduces the expense of expansion.
With the increase of location-based services, Web contents are being geo-tagged, and spatial keyword queries that retrieve objects satisfying both spatial and keyword conditions are gaining in prevalence. Unfortunatel...
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Unlike Emotion Cause Extraction(ECE) task which consists of pre-annotate emotions and passage, emotion-cause pair extraction(ECPE) aims at extracting potential emotions and corresponding causes in the document without...
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Unlike Emotion Cause Extraction(ECE) task which consists of pre-annotate emotions and passage, emotion-cause pair extraction(ECPE) aims at extracting potential emotions and corresponding causes in the document without the need for pre-annotations. Traditional ECPE solutions divide the extracting emotions and causes operation into two separate parts. However, separating the bidirectional dependence between emotion and cause may lose a lot of potentially useful information. In this paper, we propose a novel interactive recurrent attention network(IRAN). Our approach focuses on the bidirectional impact between emotions and causes, and extracts emotions and causes simultaneously. The information in the document can be fully exploited through multiple modeling and information extraction. Our emotion-specific transformation and distance fusion correlation can adaptively focus on the emotions and the distance, gracefully incorporate them into a distinguishable neural network attention framework. The experimental results show that our proposed model achieves better performance than other widely-used models on the ECPE corpus.
Serialization and deserialization play a dominant role in the state transfer time of serverless workflows, leading to substantial performance penalties during workflow execution. We identify the key reason as a lack o...
Benefiting from Pre-trained Language Model (PLM), Event Argument Extraction (EAE) methods have achieved SOTA performance in general scenarios of Event Extraction (EE). However, with increasing concerns and regulations...
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One of the most important topics in Human-Centered Computing (HCC) is to recognise human's activities. In this paper, the technology of wireless-based activity recognition is introduced. By using wireless signals,...
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ISBN:
(纸本)9781509006212
One of the most important topics in Human-Centered Computing (HCC) is to recognise human's activities. In this paper, the technology of wireless-based activity recognition is introduced. By using wireless signals, one can achieve Non-Line-Of-Sight (NLOS) recognition without carrying any devices. Also, it is easy to deploy a wireless-based recognition system due to the ubiquity of wireless communication systems. The basic idea is to detect different characteristics of signal propagation that correspond to the distinct human behaviors. As a result, action recognition is performed by analyzing the distinguishable features of signal propagation. This paper introduces the basic principles and applications of wireless-based activity recognition, and discusses the challenges and related performance metrics. Finally, open problems are discussed to point out the future research trends.
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