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CloudNMF:A MapReduce Implementation of Nonnegative Matrix Factorization for Large-scale Biological Datasets

Genomics, Proteomics & Bioinformatics 2014年第1期12卷 48-51页

作者： Ruiqi Liao Yifan Zhang Jihong Guan Shuigeng Zhou School of Computer Science Fudan University Department of Computer Science and Technology Tongji University Shanghai Key Laboratory of Intelligent Information Processing Fudan University

In the past decades,advances in high-throughput technologies have led to the generation of huge amounts of biological data that require analysis and ***,nonnegative matrix factorization （NMF） has been introduced as an efficient way to reduce the complexity of data as well as to interpret them,and has been applied to various fields of biological *** this paper,we present CloudNMF,a distributed open-source implementation of NMF on a MapReduce *** evaluation demonstrated that CloudNMF is scalable and can be used to deal with huge amounts of data,which may enable various kinds of a high-throughput biological data analysis in the *** is freely accessible at http：//***/projects/***.

关键词： Nonnegative matrix factorization MapReduce Bioinformatics

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IMAGE SEQUENCE CODING BY SPLIT AND MERGE

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IEEE TRANSACTIONS ON COMMUNICATIONS 1991年第12期39卷 1845-1855页

作者： WILLEMIN, P REED, TR KUNT, M Signal and Image Processing Laboratory Swiss Federal Institute of Technology Lausanne Switzerland Department of Electrical Engineering and Computer Science University of California Davis CA USA

This paper describes a method for reducing the information contained in an image sequence, while retaining the information necessary for the interpretation of the sequence by a human observer. The method consists of first locating the redundant information, reducing the degree of redundancy, and coding the result. The sequence is treated as a single 3-D data volume, the voxels of which are grouped into several regions, obtained by a 3-D split and merge algorithm. To find these regions, we first obtain an initial region space by splitting the image sequence until the gray-level variation over each region can be approximated by a 3-D polynomial, to a specified accuracy. This results in a set of parallelepipedic regions of various sizes. To represent the gray-level variation over these regions, the coefficients of the approximating polynomial are used as features. The most similar regions are then merged, using a region adjacency graph. The information is coded by representing the borders of the regions using a pyramidal structure in the x, y, t space. The coefficients of the approximating polynomials are coded in a straightforward manner. For 256 x 256 pixel, 25 frames/s image sequences, compressions allowing transmission rates near 64 kbit/s are obtained.

关键词： Image sequences Image coding Pixel Bandwidth Layout Polynomials Image segmentation Humans Helium ISDN

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Efficiency-Controllable Random Walks on a Class of Recursive Scale-Free Trees with a Deep Trap

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Chinese Physics Letters 2015年第3期32卷 13-16页

作者：李玲关佶红周水庚 Department of Computer Science and Technology Tongji University Shanghai 201804 Department of Basic Courses Zhejiang Shuren University Hangzhou 310015 School of Computer Science Fudan University Shanghai 200433 Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai 200433

Controls, especially effficiency controls on dynamical processes, have become major challenges in many complex systems. We study an important dynamical process, random walk, due to its wide range of applications for modeling the transporting or searching process. For lack of control methods for random walks in various structures, a control technique is presented for a class of weighted treelike scale-free networks with a deep trap at a hub node. The weighted networks are obtained from original models by introducing a weight parameter. We compute analytically the mean first passage time （MFPT） as an indicator for quantitatively measurinM the et^ciency of the random walk process. The results show that the MFPT increases exponentially with the network size, and the exponent varies with the weight parameter. The MFPT, therefore, can be controlled by the weight parameter to behave superlinearly, linearly, or sublinearly with the system size. This work provides further useful insights into controllinM eftlciency in scale-free complex networks.

关键词： Efficiency-Controllable Random Walks on a Class of Recursive Scale-Free Trees with a Deep Trap

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Improving Parallel Corpus Quality for Chinese-Vietnamese Statistical Machine Translation

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Journal of Beijing Institute of technology 2018年第1期27卷 127-136页

作者： Huu-anh Tran Yuhang Guo Ping Jian Shumin Shi Heyan Huang Department of Computer Science and Technology Beijing Institute of Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Application Beijing Institute of Technology

The performance of a machine translation system heavily depends on the quantity and quality of the bilingual language resource. However,getting a parallel corpus,which has a large scale and is of high quality,is a very difficult task especially for low resource languages such as Chinese-Vietnamese. Fortunately,multilingual user generated contents（ UGC）,such as bilingual movie subtitles,provide us access to automatic construction of the parallel corpus. Although the amount of UGC parallel corpora can be considerable,the original corpus is not suitable for statistical machine translation（ SMT） systems. The corpus may contain translation errors,sentence mismatching,free translations,etc. To improve the quality of the bilingual corpus for SMT systems,three filtering methods are proposed： sentence length difference,the semantic of sentence pairs,and machine learning. Experiments are conducted on the Chinese to Vietnamese translation *** results demonstrate that all the three methods effectively improve the corpus quality,and the machine translation performance（ BLEU score） can be improved by 1. 32.

关键词： parallel corpus filtering low resource languages bilingual movie subtitles machine translation Chinese-Vietnamese translation

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Encoding Spatial Context for Large-Scale Partial-Duplicate Web Image Retrieval

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Journal of computer science & technology 2014年第5期29卷 837-848页

作者：周文罡李厚强卢亦娟田奇 Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Department of Electronic Engineering and Information Science University of Science and Technology of China Department of Computer Science Texas State UniversitySan Marcos TX 78666 U.S.A. MemberACMIEEE Department of Computer Science University of Texas at San AntonioSan Antonio TX 78249 U.S.A. Senior MemberIEEE

Many recent state-of-the-art image retrieval approaches are based on Bag-of-Visual-Words model and represent an image with a set of visual words by quantizing local SIFT（scale invariant feature transform） features. Feature quantization reduces the discriminative power of local features and unavoidably causes many false local matches between images, which degrades the retrieval accuracy. To filter those false matches, geometric context among visual words has been popularly explored for the verification of geometric consistency. However, existing studies with global or local geometric verification are either computationally expensive or achieve limited accuracy. To address this issue, in this paper, we focus on partialduplicate Web image retrieval, and propose a scheme to encode the spatial context for visual matching verification. An efficient affine enhancement scheme is proposed to refine the verification results. Experiments on partial-duplicate Web image search, using a database of one million images, demonstrate the effectiveness and efficiency of the proposed *** on a 10-million image database further reveals the scalability of our approach.

关键词： large-scale image retrieval spatial context coding spatial verification affine estimation

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Optimal location query based on k nearest neighbours

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Frontiers of computer science 2021年第2期15卷 105-117页

作者： Yubao LIU Zitong CHEN Ada Wai-Chee FU Raymond Chi-Wing WONG Genan DAI School of Data and Computer Science Sun Yat-Sen UniversityGuangzhou510006China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou510006China Department of Computer Science and Engineering Chinese University of Hong KongHong Kong999077China Department of Computer Science and Engineering The Hong Kong University of Science and TechnologyHong Kong999077China

Optimal location query in road networks is a basic operation in the location intelligence *** a set of clients and servers on a road network,the purpose of optimal location query is to obtain a location for a new server,so that a certain objective function calculated based on the locations of clients and servers is *** works assume no labels for servers and that a client only visits the nearest *** assumptions are not realistic and it renders the existing work not useful in many *** this paper,we relax these assumptions and consider the k nearest neighbours(KNN)of *** introduce the problem of KNN-based optimal location query(KOLQ)which considers the k nearest servers of clients and labeled *** also introduce a variant problem called relocation KOLQ(RKOLQ)which aims at relocating an existing server to an optimal *** main analysis algorithms are proposed for these *** experiments on the real road networks illustrate the efficiency of our proposed solutions.

关键词： optimal location query k nearest neighbours road network

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Few-Shot Object Detection Based on the Transformer and High-Resolution Network

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computers, Materials & Continua 2023年第2期74卷 3439-3454页

作者： Dengyong Zhang Huaijian Pu Feng Li Xiangling Ding Victor S.Sheng Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan411004China Department of Computer Science Texas Tech UniversityLubbock79409TXUSA

Now object detection based on deep learning tries different *** uses fewer data training networks to achieve the effect of large dataset ***,the existing methods usually do not achieve the balance between network parameters and training *** makes the information provided by a small amount of picture data insufficient to optimize model parameters,resulting in unsatisfactory detection *** improve the accuracy of few shot object detection,this paper proposes a network based on the transformer and high-resolution feature extraction(THR).High-resolution feature extractionmaintains the resolution representation of the *** and spatial attention are used to make the network focus on features that are more useful to the *** addition,the recently popular transformer is used to fuse the features of the existing *** compensates for the previous network failure by making full use of existing object *** on the Pascal VOC and MS-COCO datasets prove that the THR network has achieved better results than previous mainstream few shot object detection.

关键词： Object detection few shot object detection transformer high-resolution

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A Gradient-Guided Evolutionary Approach to Training Deep Neural Networks

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2022年第9期33卷 4861-4875页

作者： Yang, Shangshang Tian, Ye He, Cheng Zhang, Xingyi Tan, Kay Chen Jin, Yaochu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei China Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Department of Computing The Hong Kong Polytechnic University Hong Kong SAR Department of Computer Science University of Surrey Guildford U.K

It has been widely recognized that the efficient training of neural networks (NNs) is crucial to classification performance. While a series of gradient-based approaches have been extensively developed, they are criticized for the ease of trapping into local optima and sensitivity to hyperparameters. Due to the high robustness and wide applicability, evolutionary algorithms (EAs) have been regarded as a promising alternative for training NNs in recent years. However, EAs suffer from the curse of dimensionality and are inefficient in training deep NNs (DNNs). By inheriting the advantages of both the gradient-based approaches and EAs, this article proposes a gradient-guided evolutionary approach to train DNNs. The proposed approach suggests a novel genetic operator to optimize the weights in the search space, where the search direction is determined by the gradient of weights. Moreover, the network sparsity is considered in the proposed approach, which highly reduces the network complexity and alleviates overfitting. Experimental results on single-layer NNs, deep-layer NNs, recurrent NNs, and convolutional NNs (CNNs) demonstrate the effectiveness of the proposed approach. In short, this work not only introduces a novel approach for training DNNs but also enhances the performance of EAs in solving large-scale optimization problems.

关键词： Artificial neural networks Training Optimization Search problems Scalability Complexity theory Genetic algorithms Deep neural networks (DNNs) evolutionary algorithm (EA) genetic operator gradient descent sparsity

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A new approach for modeling OOV words 6

A new approach for modeling OOV words

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6th International Conference on Spoken Language processing, ICSLP 2000

作者： Ren, Weimin Wang, Chengfa Gao, Wen Xu, Jinpei Speech Processing Laboratory Department of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)7801501144

This paper addressed the problem of Out-Of-Vocabulary (OOV) utterance detection in small vocabulary telephone keyword spotting system. We propose a new approach for modeling OOV words in the scenario of a small vocabulary of telephone keyword spotting system. The paper adopt the semi-continuous Hidden Markov Model with multiple codebooks to modeling the keywords. We propose a two pass procedure to spot the real keyword occurrence. In the first pass, the normal viterbi search procedure is applied, with the appropriate defined and trained garbage models and silence models. The output of this stage produces the N-best word hypothesis The second pass, which can be seen as a verification procedure, take the first pass output as focuses. This approach is mainly constructing a "dynamic anti-model" based on the detected hypothesis keyword model and the current input acoustic information.

关键词： Telephone sets

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NVLAN: A Novel VLAN technology for Scalable Multi-tenant Datacenter Networks 2

NVLAN: A Novel VLAN Technology for Scalable Multi-tenant Dat...

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2nd International Conference on Advanced Cloud and Big Data, CBD 2014

作者： Hu, Yang Li, Huiba Peng, Yuxing Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Computer Science Department China

ISBN: (纸本)9781479980857

Nowadays, cloud providers of 'Infrastructure as a service' require datacenter networks to support virtualization and multi-tenancy at large scale, while it brings a grand challenge to datacenters. Traditional network technologies of datacenters and common commodity devices of network can not meet these new needs. In this paper, we present NVLAN, a novel VLAN technology for scalable multi-tenant datacenter networks. NVLAN eliminates the quantity limitation of logic isolated networks on VLAN through a slight modification. NVLAN can be applied to very large-scale datacenter networks, without the need of expensive and dedicated switches. Through encapsulation of tenant's packets, NVLAN provides tenants with full address space virtualization to configure their own logic network. We implemented NVLAN on a test bed, and demonstrated that it can be scaled up to large numbers of multi-tenant networks with negligible overhead. © 2014 IEEE.

关键词： Virtualization

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