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14th International Conference on Bio-inspired computing: Theories and Applications, BIC-TA 2019

作者： Sun, Dengdi Sun, Haifeng Wu, Hang Liang, Huadong Ding, Zhuanlian Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China iFlytek Co. Ltd. Hefei230088 China School of Internet Anhui University Hefei230039 China

ISBN: (纸本)9789811534140

Determining the functional roles of proteins is a vital task to understand life at molecular level and has great biomedical and pharmaceutical implications. With the development of novel high-throughput techniques, enormous amounts of protein-protein interaction (PPI) data are collected and provide an important and feasible way for studying protein function predictions. According to this, many approaches assign biological functions to all proteins using PPI networks directly. However, due to the extreme complexity of the topology structure of real PPI networks, it is very difficult and time consuming to seek the global optimization or clustering on the networks. In addition, biological functions are often highly correlated, which makes functions assigned to proteins are not independent. To address these challenges, in this paper we propose a two-stage function annotation method with robust feature selection. First, we transform the network into the low-dimensional representations of nodes via manifold learning. Then, we integrate the functional correlation into the framework of multi-lab.l linear regression, and introduce robust sparse penalty to achieve the function assignment and representative feature selection simultaneously. For the optimization, we design an efficient algorithm to iteratively solve several subproblems with closed-form solutions. Extensive experiments against other baseline methods on Saccharomyces cerevisiae data demonstrate the effectiveness of the proposed approach. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Proteins

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AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation 38

AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmenta...

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38th Conference on Neural Information processing Systems, NeurIPS 2024

作者： Han, Boyu Xu, Qianqian Yang, Zhiyong Bao, Shilong Wen, Peisong Jiang, Yangbangyan Huang, Qingming Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS China School of Computer Science and Tech. University of Chinese Academy of Sciences China Peng Cheng Laboratory China Key Laboratory of Big Data Mining and Knowledge Management CAS China

The Area Under the ROC Curve (AUC) is a well-known metric for evaluating instance-level long-tail learning problems. In the past two decades, many AUC optimization methods have been proposed to improve model performance under long-tail distributions. In this paper, we explore AUC optimization methods in the context of pixel-level long-tail semantic segmentation, a much more complicated scenario. This task introduces two major challenges for AUC optimization techniques. On one hand, AUC optimization in a pixel-level task involves complex coupling across loss terms, with structured inner-image and pairwise inter-image dependencies, complicating theoretical analysis. On the other hand, we find that mini-batch estimation of AUC loss in this case requires a larger batch size, resulting in an unaffordable space complexity. To address these issues, we develop a pixel-level AUC loss function and conduct a dependency-graph-based theoretical analysis of the algorithm's generalization ability. Additionally, we design a Tail-Classes Memory Bank (T-Memory Bank) to manage the significant memory demand. Finally, comprehensive experiments across various benchmarks confirm the effectiveness of our proposed AUCSeg method. The code is availab.e at https://***/boyuh/AUCSeg. © 2024 Neural information processing systems foundation. All rights reserved.

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Detecting coordinated regulations of pathways by higher logic analysis

Detecting coordinated regulations of pathways by higher logi...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yansen Su Xingyi Zhang Linqiang Pan Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781509016129

Non-small cell lung cancer (NSCLC) is a malignant tumor, and contains three major subtypes which are difficult to be distinguished at early stages of NSCLC. Many pathways work together to perform certain functions in cells. One might expect the high level of co-appearance or repression of pathways to distinguish different subtypes of NSCLC. However, it is difficult to detect coordinated regulations of pathways by existing methods. In our work, the coordinated regulations of pathways are detected using modified higher logic analysis of gene expression data. Specifically, we identify the genes whose regulation obeys a logic function by the modified higher logic analysis, which focuses on the relationships among the gene triplets that are not evident when genes are examined in a pairwise fashion. Then, the relationships among genes are mapped to pathways to predict the coordinated regulated relationships among pathways. By comparing coordinated regulations of pathways, we find that the regulation patterns of pathways which are associated with cell death are different in three subtypes of NSCLC. This method allows us to uncover co-appearance or repression of pathways in high level, and it has a potential to distinguish the subtypes for complex diseases.

关键词： Cancer Lungs

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A novel miniaturized l-band filter with great stopband characteristics using interdigitated coupled lines CRLH-TL structure

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Progress In Electromagnetics Research C 2021年 114卷 57-67页

作者： Wang, Peng Duan, Kaiyue Li, Minquan Zhang, Man Jin, Baokun Anqing Normal University Anqing246011 China Key Lab of Ministry of Education of Intelligent Computing & Signal Processing Anhui University Hefei230601 China

This paper proposes a novel bandpass filter for L-band based on CRLH TL, which is mainly formed by coupling a high-pass characteristic module with a low-pass characteristic module in a cascade. The high-pass module consists of an interdigitated coupled line and a grounding via, owning to its singular characteristics, which the miniaturization is realized. The low-pass module is composed of a C-type resonator with high-low impedance lines, which can realize great sideband attenuation characteristics. To further improve its out-of-band rejection characteristics, a complementary split-ring resonator (CSRR) defective ground structure with single-pole attenuation characteristics is loaded, and a transmission zero is introduced at 2.5f0 out-of-band. The test results are in great agreement with the simulation ones, and the dimensions are only 0.20λg * 0.22λg. Compared with other similar types, the filter proposed in this paper has miniaturization, great passband selection characteristics, stopband characteristics, and the advantage of low insertion loss. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Bandpass filters

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Cross-view graph embedding

Cross-view graph embedding

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11th Asian Conference on Computer Vision, ACCV 2012

作者： Huang, Zhiwu Shan, Shiguang Zhang, Haihong Lao, Shihong Chen, Xilin Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China OMRON Social Solutions Co. Ltd. Kyoto Japan

ISBN: (纸本)9783642374432

Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) under the proposed framework. Different from previous cross-view methods only preserving inter-view discriminant information or the intra-view local structure, CLODA preserves the local structure and the discriminant information of both intra-view and inter-view. Extensive experiments are conducted to evaluate our algorithms on two cross-view face recognition problems: face recognition across poses and face recognition across resolutions. These real-world face recognition experiments demonstrate that our framework achieves impressive performance in the cross-view problems. © 2013 Springer-Verlag.

关键词： Face recognition

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Reducing blocking artifacts in compressed images via transform-domain non-local coefficients estimation

Reducing blocking artifacts in compressed images via transfo...

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2012 13th IEEE International Conference on Multimedia and Expo, ICME 2012

作者： Zhang, Xinfeng Xiong, Ruiqin Ma, Siwei Gao, Wen Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China Institute of Digital Media Peking University Beijing 100871 China

ISBN: (纸本)9781467316590

Block transform coding using discrete cosine transform is the most popular approach for image compression. However, many annoying blocking artifacts are generated due to coarse quantization on transform coefficients independently. This paper proposes an effective blocking artifacts reduction method by estimating the transform coefficients from their quantized version. In the proposed scheme, we estimate the transform coefficients based on an image statistic model and non-local similarity among blocks in transform domain. The parameters used in our proposed scheme are discussed and adaptively selected. Extensive experimental results show that our proposed method significantly reduces blocking artifacts and improves the subjective and the objective quality of block transform coded images. © 2012 IEEE.

关键词： Discrete cosine transforms

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High-order parabolic equation method for electromagnetic computation

High-order parabolic equation method for electromagnetic com...

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2008 Asia Pacific Microwave Conference, APMC 2008

作者： Huang, Zhi-Xiang Bo, Wu Wei, Sha Chen, Ming-Sheng Wu, Xian-Liang Hong, Dai Key Lab of Intelligent Computing and Signal Processing Anhui University China School of physical science and technology Yunnan University China Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong Department of Physics and Electronic Engineering Hefei Teachers College China

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Good Lattice Swarm Algorithm for Constrained Engineering Design Optimization

Good Lattice Swarm Algorithm for Constrained Engineering Des...

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第三届IEEE无线通讯、网络技术暨移动计算国际会议

作者： Shoubao Su Jiwen Wang Wangkang Fan Xibing Yin Key Lab of Intelligent Computing & Signal Processing of the National Education Ministry Anhui Unive Key Lab of Intelligent Computing & Signal Processing of the National Education Ministry Anhui Unive Gear Institute of Lu'an Automotive Gear Manufacture Co. Ltd Anhui Jianghuai Automotive Group Lu'an

Engineering optimization in the intelligence swarm remains to be a challenge. Recently, a novel optimization method based on number-theory and particle swarm, good lattice swarm optimization algorithm(GLSO), is introduced, which intends to produce faster and better global search ability and more accurate convergence because it has a solid theoretical basis. In this paper, four models of constructing good point set are introduced and the GLSO based on new models is rewritten. Some applications of the new model on constrained engineering via employing a penalty function approach suggest that the presented algorithm is potentially a powerful search technique for solving complex engineering design optimization problems.

关键词： good lattice points particle swarm optimization constrained engineering optimization penalty function.

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PPLSA: Parallel probabilistic latent semantic analysis based on MapReduce

PPLSA: Parallel probabilistic latent semantic analysis based...

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7th IFIP International Conference on intelligent Information processing, IIP 2012

作者： Li, Ning Zhuang, Fuzhen He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate University Chinese Academy of Sciences Beijing China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding China

ISBN: (纸本)9783642328909

PLSA(Probabilistic Latent Semantic Analysis) is a popular topic modeling technique for exploring document collections. Due to the increasing prevalence of large datasets, there is a need to improve the scalab.lity of computation in PLSA. In this paper, we propose a parallel PLSA algorithm called PPLSA to accommodate large corpus collections in the MapReduce framework. Our solution efficiently distributes computation and is relatively simple to implement. © 2012 IFIP International Federation for Information processing.

关键词： MapReduce

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A META-SEARCH ENGINE BASED ON QUOTIENT SPACE

A META-SEARCH ENGINE BASED ON QUOTIENT SPACE

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2005中国宁波国际计算机科学与技术学术大会

作者： Wei-min Yang Long-shu Li Ministry of Education Key Lab of Intelligent Computing and Signal Processing at Anhui University Department of Computer Science and Engineering Anhui University

World Wide Web has developed to an inherently distributed information system,which brings people great trouble in finding needed information although huge amount of information availab.e on the *** search engine is a very important tool for people to obtain information on the webs,but the low-precision and low-recall exist widely in current search *** effective and accurate intelligent search engine based on the expert systems technology has become the most important research *** paper analyzes the WWW with different granularities according to quotient space theory,gives summarization of search engine and describes an expert system built by Visual Prolog.

关键词： Quotient space Search engine Expert system Visual Prolog.

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