检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Zhang, Jianing Wei, Chong Han, Yongming Lei, Dewen State Key Laboratory of Loess and Quaternary Geology Key Lab of Aerosol Chemistry and Physics Institute of Earth Environment Chinese Academy of Sciences Xi’an710061 China Shanghai Carbon Data Research Center CAS Key Laboratory of Low-Carbon Conversion Science and Engineering Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai201210 China Department of Environmental Science and Technology School of Human Settlements and Civil Engineering Xi’an Jiaotong University Xi’an710049 China University of Chinese Academy of Sciences Beijing100049 China

Polycyclic aromatic compounds (PACs), such as polycyclic aromatic hydrocarbons (PAHs,) and their derivatives (oxygenated PAHs, nitrated PAHs and N-heterocyclic PAHs), have received extensive attention due to their carcinogenicity, teratogenicity, and mutagenicity to humans. In this study, gaseous and PM2.5-bound PACs were analysed in four seasons in 2016 in Xi’an and further evaluated for their gas/particle partition, sources, and health risks. Annual average concentrations (gaseous + particulate) of Σ27PAHs, Σ12OPAHs, Σ14NPAHs, and Σ4AZAs were 445.1±428.0, 45.6±62.4, 4.9±6.5, and 6.2±8.6 ng m−3, respectively, with the highest values in winter and the lowest values in summer. Low-molecular-weight PACs mainly occur in gaseous and high-molecular-weight PACs partition in particles, and the major mechanism is absorption into the atmospheric particles. PACs significantly correlated with combustion-derived air pollutants and carbon fractions, suggesting their common sources and transport pathways. The concentration ratios indicated mixed sources of fossil fuel combustion and biomass burning, while the positive matrix factorization model suggested that coal combustion, vehicle exhaust, and biomass burning accounted for 30.0%, 25.8% and 23.6% of PAHs, respectively, and direct emissions contributed 56.1% of OPAHs. The PACs estimated annual lifetime lung cancer risk is 2.67 × 10−5, exceeding the value advocated by the World Health Organization (10−5). © 2023, The Authors. All rights reserved.

关键词： Polycyclic aromatic hydrocarbons

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Uncertainty calibration for ensemble-based debiasing methods

arXiv

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arXiv 2021年

作者： Xiong, Ruibin Chen, Yimeng Pang, Liang Cheng, Xueqi Ma, Zhiming Lan, Yanyan CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Baidu Inc Academy of Mathematics and Systems Science Chinese Academy of Sciences Data Intelligence System Research Center Institute of Computing Technology Chinese Academy of Sciences Institute for AI Industry Research Tsinghua University

Ensemble-based debiasing methods have been shown effective in mitigating the reliance of classifiers on specific dataset bias, by exploiting the output of a bias-only model to adjust the learning target. In this paper, we focus on the bias-only model in these ensemble-based methods, which plays an important role but has not gained much attention in the existing literature. Theoretically, we prove that the debiasing performance can be damaged by inaccurate uncertainty estimations of the bias-only model. Empirically, we show that existing bias-only models fall short in producing accurate uncertainty estimations. Motivated by these findings, we propose to conduct calibration on the bias-only model, thus achieving a three-stage ensemble-based debiasing framework, including bias modeling, model calibrating, and debiasing. Experimental results on NLI and fact verification tasks show that our proposed three-stage debiasing framework consistently outperforms the traditional two-stage one in out-of-distribution accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Calibration

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Eigen microstates and their evolutions in complex systems

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Communications in Theoretical Physics 2021年第6期73卷 140-157页

作者： Yu Sun Gaoke Hu Yongwen Zhang Bo Lu Zhenghui Lu Jingfang Fan Xiaoteng Li Qimin Deng Xiaosong Chen Institute of Theoretical Physics Key Laboratory of Theoretical PhysicsChinese Academy of SciencesPO Box 2735Beijing 100190China School of Physical Sciences University of Chinese Academy of ScienceNo.19A Yuquan RoadBeijing 100049China Beijing Computational Science Research Center Beijing 100193China Data Science Research Center Kunming University of Science and TechnologyKunming 650500China Laboratory for Climate Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China CAS Key Laboratory of Regional Climate Environment for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China School of Systems Science Beijing Normal UniversityBeijing 100875China Harvest Fund Management Beijing 100021China Lab for Climate and Ocean-Atmosphere Studies Deptof Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing100871China

Emergence refers to the existence or formation of collective behaviors in complex ***,we develop a theoretical framework based on the eigen microstate theory to analyze the emerging phenomena and dynamic evolution of complex *** this framework,the statistical ensemble composed of M microstates of a complex system with N agents is defined by the normalized N×M matrix A,whose columns represent microstates and order of row is consist with the *** ensemble matrix A can be decomposed as■,where r=min(N,M),eigenvalueσIbehaves as the probability amplitude of the eigen microstate U_I so that■and U_I evolves following V_*** a disorder complex system,there is no dominant eigenvalue and eigen *** a probability amplitudeσIbecomes finite in the thermodynamic limit,there is a condensation of the eigen microstate UIin analogy to the Bose–Einstein condensation of Bose *** indicates the emergence of U_I and a phase transition in complex *** framework has been applied successfully to equilibrium threedimensional Ising model,climate system and stock *** anticipate that our eigen microstate method can be used to study non-equilibrium complex systems with unknown orderparameters,such as phase transitions of collective motion and tipping points in climate systems and ecosystems.

关键词： complex system phase transition critical phenomena Earth system statistical ensemble eigen microstate dynamic evolution econophysics

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An enhanced MinHash encryption scheme for encrypted deduplication

An enhanced MinHash encryption scheme for encrypted deduplic...

引用

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Qiaowen Jia Guanxiong Ha Hanwei Wang Haoyu Ma Hang Chen State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China College of Cyber Science Nankai University Tianjin China Tianjin Key Laboratory of Network and Data Security Technology Tianjin China Zhejiang Lab Hangzhou China The School of Cyber Engineering Xidian University Xi’an China

The encrypted deduplication can provide both storage savings and data confidentiality for cloud storage systems. Convergent encryption (CE) is a well-known solution for encrypted deduplication, but it brings huge computation and storage overheads for key management. MinHash encryption is an effective solution to this issue. It reduces the number of keys by grouping multiple consecutive chunks into segments and generating one key for each segment. However, MinHash encryption does not take full advantage of the segment similarity, which can be used to further reduce the overhead for key management. To this end, we augment MinHash encryption with Bloom filter and Locality Sensitivity Hash (LSH) to design an enhanced MinHash encryption scheme. Firstly, our scheme generates a sketch for each segment based on the Bloom filter, and projects sketches to the points in a hash table through LSH functions. Secondly, we detect the segment similarity by the distance between points, and similar segments are grouped into super-segments. Finally, we combine MinHash encryption and server-aided message-locked encryption to encrypt the super-segments for achieving encrypted deduplication. We conduct trace-driven experiments using a realworld dataset. Compared with MinHash encryption, our scheme has higher storage efficiency and better encryption performance.

关键词： Privacy Maximum likelihood estimation data privacy Cloud computing Sensitivity Encryption

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Conditional GANs with Auxiliary Discriminative Classifier

arXiv

引用

arXiv 2021年

作者： Hou, Liang Cao, Qi Shen, Huawei Pan, Siyuan Li, Xiaoshuang Cheng, Xueqi Data Intelligence System Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Shanghai Jiao Tong University Shanghai China CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China

Conditional generative models aim to learn the underlying joint distribution of data and labels to achieve conditional data generation. Among them, the auxiliary classifier generative adversarial network (AC-GAN) has been widely used, but suffers from the problem of low intra-class diversity of the generated samples. The fundamental reason pointed out in this paper is that the classifier of AC-GAN is generator-agnostic, which therefore cannot provide informative guidance for the generator to approach the joint distribution, resulting in a minimization of the conditional entropy that decreases the intra-class diversity. Motivated by this understanding, we propose a novel conditional GAN with an auxiliary discriminative classifier (ADC-GAN) to resolve the above problem. Specifically, the proposed auxiliary discriminative classifier becomes generator-aware by recognizing the class-labels of the real data and the generated data discriminatively. Our theoretical analysis reveals that the generator can faithfully learn the joint distribution even without the original discriminator, making the proposed ADC-GAN robust to the value of the coefficient hyperparameter and the selection of the GAN loss, and stable during training. Extensive experimental results on synthetic and real-world datasets demonstrate the superiority of ADC-GAN in conditional generative modeling compared to state-of-the-art classifier-based and projection-based conditional GANs. Copyright © 2021, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Query understanding via intent description generation

arXiv

引用

arXiv 2020年

作者： Zhang, Ruqing Guo, Jiafeng Fan, Yixing Lan, Yanyan Cheng, Xueqi CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

Query understanding is a fundamental problem in information retrieval (IR), which has attracted continuous attention through the past decades. Many different tasks have been proposed for understanding users’ search queries, e.g., query classification or query clustering. However, it is not that precise to understand a search query at the intent class/cluster level due to the loss of many detailed information. As we may find in many benchmark datasets, e.g., TREC and SemEval, queries are often associated with a detailed description provided by human annotators which clearly describes its intent to help evaluate the relevance of the documents. If a system could automatically generate a detailed and precise intent description for a search query, like human annotators, that would indicate much better query understanding has been achieved. In this paper, therefore, we propose a novel Query-to-Intent-Description (Q2ID) task for query understanding. Unlike those existing ranking tasks which leverage the query and its description to compute the relevance of documents, Q2ID is a reverse task which aims to generate a natural language intent description based on both relevant and irrelevant documents of a given query. To address this new task, we propose a novel Contrastive Generation model, namely CtrsGen for short, to generate the intent description by contrasting the relevant documents with the irrelevant documents given a query. We demonstrate the effectiveness of our model by comparing with several state-of-the-art generation models on the Q2ID task. We discuss the potential usage of such Q2ID technique through an example application. Copyright © 2020, The Authors. All rights reserved.

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Adversarial Immunization for Certifiable Robustness on Graphs

arXiv

引用

arXiv 2020年

作者： Tao, Shuchang Shen, Huawei Cao, Qi Hou, Liang Cheng, Xueqi CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

Despite achieving strong performance in semi-supervised node classification task, graph neural networks (GNNs) are vulnerable to adversarial attacks, similar to other deep learning models. Existing researches focus on developing either robust GNN models or attack detection methods against adversarial attacks on graphs. However, little research attention is paid to the potential and practice of immunization to adversarial attacks on graphs. In this paper, we propose and formulate the graph adversarial immunization problem, i.e., vaccinating an affordable fraction of node pairs, connected or unconnected, to improve the certifiable robustness of graph against any admissible adversarial attack. We further propose an effective algorithm, called AdvImmune, which optimizes with meta-gradient in a discrete way to circumvent the computationally expensive combinatorial optimization when solving the adversarial immunization problem. Experiments are conducted on two citation networks and one social network. Experimental results demonstrate that the proposed AdvImmune method remarkably improves the ratio of robust nodes by 12%, 42%, 65%, with an affordable immune budget of only 5% edges. Copyright © 2020, The Authors. All rights reserved.

关键词： Graph neural networks

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ICTNET at Trec 2019 Conversational Assistance Track 28

ICTNET at Trec 2019 Conversational Assistance Track

引用

28th Text REtrieval Conference, TREC 2019

作者： Hao, Changying Zhang, Yuanyuan Yang, Weifeng Zhao, Heng CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

In this paper we report on our participation in the TREC 2019 Conversational Assistance Track which focuses on Conversational Information Seeking（CIS）namely understand the dialogue context and retrieve candidate response information from collections provided. We convert the CIS task into a standard information retrieval task and use both traditional IR model and neural IR model to rerank the baseline official evaluation results. We compare the results of models in two categories(four models in total), and give a summary for the solution of our work. © 2019 28th Text REtrieval Conference, TREC 2019 - Proceedings. All Rights Reserved.

关键词： Information retrieval

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Strong quantum nonlocality without entanglement in multipartite quantum systems

引用

Physical Review A 2020年第4期102卷 042228-042228页

作者： Pei Yuan Guojing Tian Xiaoming Sun CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100049 China CAS Center of Excellence in Topological Quantum Computation Beijing 100049 China

In this paper, we generalize the concept of strong quantum nonlocality from two aspects. First, in a tripartite quantum system, we present a construction of strongly nonlocal quantum states containing 6(d−1)2 orthogonal product states in Cd⊗Cd⊗Cd and build 6d2−8d+4 product states in Cd⊗Cd⊗Cd+1, which have been proved to be strongly nonlocal. Obviously, both results turn out to be one order of magnitude smaller than the number of basis states d3 for d≥3. Second, we give explicit forms of strongly nonlocal orthogonal product basis in C3⊗C3⊗C3⊗C3 and C4⊗C4⊗C4⊗C4 quantum systems, where four is the largest known number of subsystems in which there exists strong quantum nonlocality without entanglement up to now. All the results positively answer the open problems raised by Halder et al. [Phys. Rev. Lett. 122, 040403 (2019)]; that is, there do exist a small number of quantum states that can demonstrate strong quantum nonlocality without entanglement.

关键词： Nonlocality

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MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization

arXiv

引用

arXiv 2022年

作者： Duan, Yue Zhao, Zhen Qi, Lei Wang, Lei Zhou, Luping Shi, Yinghuan Gao, Yang The National Key Laboratory for Novel Software Technology The National Institute of Healthcare Data Science Nanjing University Nanjing210023 China The School of Electrical and Information Engineering The University of Sydney SydneyNSW2006 Australia The School of Computer Science and Engineering The Key Lab of Computer Network and Information Integration Ministry of Education Southeast University Nanjing211189 China The School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia

The core issue in semi-supervised learning (SSL) lies in how to effectively leverage unlabeled data, whereas most existing methods tend to put a great emphasis on the utilization of high-confidence samples yet seldom fully explore the usage of low-confidence samples. In this paper, we aim to utilize low-confidence samples in a novel way with our proposed mutex-based consistency regularization, namely MutexMatch. Specifically, the high-confidence samples are required to exactly predict "what it is" by conventional True-Positive Classifier, while low-confidence samples are employed to achieve a simpler goal — to predict with ease "what it is not" by True-Negative Classifier. In this sense, we not only mitigate the pseudo-labeling errors but also make full use of the low-confidence unlabeled data by consistency of dissimilarity degree. MutexMatch achieves superior performance on multiple benchmark datasets, i.e., CIFAR-10, CIFAR-100, SVHN, STL-10, mini-ImageNet and Tiny-ImageNet. More importantly, our method further shows superiority when the amount of labeled data is scarce, e.g., 92.23% accuracy with only 20 labeled data on CIFAR-10. Our code and model weights have been released at https://***/NJUyued/MutexMatch4SSL. Copyright © 2022, The Authors. All rights reserved.

关键词： Benchmarking

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