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arXiv 2023年

作者： Dang, Zhuohang Luo, Minnan Jia, Chengyou Dai, Guang Wang, Jihong Chang, Xiaojun Wang, Jingdong The School of Computer Science and Technology The Ministry of Education Key Laboratory of Intelligent Networks and Network Security The Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi'an Jiaotong University Shaanxi Xi’an710049 China The SGIT AI Laboratory Xi’an710048 China The State Grid Shaanxi Electric Power Company Ltd. State Grid Corporation of China Xi’an710048 China The School of Information Science and Technology University of Science and Technology of China Hefei230026 China Abu Dhabi United Arab Emirates Baidu Inc Beijing100085 China

Encoding only the task-related information from the raw data, i.e., disentangled representation learning, can greatly contribute to the robustness and generalizability of models. Although significant advances have been made by regularizing the information in representations with information theory, two major challenges remain: 1) the representation compression inevitably leads to performance drop;2) the disentanglement constraints on representations are in complicated optimization. To these issues, we introduce Bayesian networks with transmitted information to formulate the interaction among input and representations during disentanglement. Building upon this framework, we propose DisTIB (Transmitted Information Bottleneck for Disentangled representation learning), a novel objective that navigates the balance between information compression and preservation. We employ variational inference to derive a tractable estimation for DisTIB. This estimation can be simply optimized via standard gradient descent with a reparameterization trick. Moreover, we theoretically prove that DisTIB can achieve optimal disentanglement, underscoring its superior efficacy. To solidify our claims, we conduct extensive experiments on various downstream tasks to demonstrate the appealing efficacy of DisTIB and validate our theoretical analyses. Copyright © 2023, The Authors. All rights reserved.

关键词： Information theory

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Special issue: Innovative applications of big data and artificial intelligence

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Frontiers of engineering Management 2022年第4期9卷 517-519页

作者： W.Art CHAOVALITWONGSE Ye YUAN Qingpeng ZHANG Jianguo LIU Department of Industrial Engineering University of ArkansasFayettevilleAR 72701USA School of Artificial Intelligence and Automation State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhan 430074China School of Data Science City University of Hong KongHong KongChina Institute of Accounting and Finance Shanghai University of Finance and EconomicsShanghai 200433China

Big data refers to complex data sets that cannot be processed using traditional data processing *** could also be defined as a large amount of unstructured or structured data from various *** intelligence(AI)refers to the science of expressing and acquiring knowledge using data,algorithms,and computing *** far,the big data industry chain is gradually mature,leading to a combination of big data and AI techniques developed in comprehensive *** cutting-edge technologies of big data and AI have played an increasingly important role in the innovative development of various industries such as epidemic prevention and control,emergency management,social governance,manufacturing,medical services,intelligent transportation,Internet of Things/supply chain,Internet industry,new media,and so *** addition,there are many typical innovative projects,which are being produced.

关键词： artificial services prevention

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Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection 39

Look Inside for More: Internal Spatial Modality Perception f...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Liang, Hanzhe Xie, Guoyang Hou, Chengbin Wang, Bingshu Gao, Can Wang, Jinbao College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen Audencia Financial Technology Institute Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Department of Intelligent Manufacturing CATL Ningde China School of Computing and Artificial Intelligence Fuyao University of Science and Technology Fuzhou China School of Software Northwestern Polytechnical University Xi’an China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen China

ISBN: (纸本)157735897X

3D anomaly detection has recently become a significant focus in computer vision. Several advanced methods have achieved satisfying anomaly detection performance. However, they typically concentrate on the external structure of 3D samples and struggle to leverage the internal information embedded within samples. Inspired by the basic intuition of why not look inside for more, we introduce a straightforward method named Internal Spatial Modality Perception (ISMP) to explore the feature representation from internal views fully. Specifically, our proposed ISMP consists of a critical perception module, Spatial Insight Engine (SIE), which abstracts complex internal information of point clouds into essential global features. Besides, to better align structural information with point data, we propose an enhanced key point feature extraction module for amplifying spatial structure feature representation. Simultaneously, a novel feature filtering module is incorporated to reduce noise and redundant features for further aligning precise spatial structure. Extensive experiments validate the effectiveness of our proposed method, achieving object-level and pixel-level AUROC improvements of 4.2% and 13.1%, respectively, on the Real3D-AD benchmarks. Note that the strong generalization ability of SIE has been theoretically proven and is verified in both classification and segmentation tasks. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Feature extraction

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REMARKS ON ASYMPTOTIC EXPANSIONS OF COMPOSITIONS WITH THE ELEMENTARY FUNCTIONS

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数学杂志 2025年第2期45卷 131-139页

作者： LUO Xiao-Yu SHI Yong-Guo JIANG Zhi-Jie College of Mathematics and Statistics Sichuan University of Science and EngineeringSichuan 64300China Data Recovery Key Laboratory of Sichuan Province College of Mathematics and Information ScienceNeijiang Normal UniversitySichuan 641100China

In this paper,we study asymptotic power series of the composition f(x)=h(g(x)),where g(x)=∑_(n=0)^(∞)b_(n)x^(-n),b_(n)∈R,and h is a given elementary *** asymptotic expansions have been obtained for the composition with an exponential or logarithmic *** the re-cursive method,we present the asymptotic expansions for the composition with seven trigonometric functions,*** an application,the asymptotic expansions of roots of some equations are *** results show that our recursive formula is more efficient than the method of Lagrange's inverse theorem.

关键词： asymptotic expansion asymptotic power series trigonometric function composite function

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Characterization of prognosis and immune infiltration by a novel glutamine metabolism-related model in cutaneous melanoma

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BIOCELL 2023年第9期47卷 1931-1945页

作者： MENGQIN ZHU TIANYI XU HAN ZHANG XIN FAN YULAN WANG JIAJIA ZHANG FEI YU Shanghai Clinical College Anhui Medical UniversityShanghai200040China The Fifth Clinical Medical College Anhui Medical UniversityHefei230032China Department of Nuclear Medicine Shanghai Tenth People’s HospitalTongji University School of MedicineShanghai200040China Institute of Nuclear Medicine Tongji University School of MedicineShanghai200040China National Genomics Data Center and CAS Key Laboratory of Genome Sciences and Information Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing100101China Department of Biomedical Engineering Nanjing University of Aeronautics and AstronauticsNanjing210000China

Glutamine metabolism(GM)plays an important role in tumor growth and *** cutaneous melanoma(SKCM)is a glutamine-dependent ***,the molecular characteristics and action mechanism of GM on SKCM remain ***,we aimed to explore the effects of GM-related genes on survival,clinicopathological characteristics,and the tumor microenvironment in *** this study,682 SKCM samples were obtained from the Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)*** clustering was used to classify SKCM samples into distinct subtypes based on 41 GM-related *** in survival,immune infiltration,clinical characteristics,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways as well as differentially expressed genes(DEGs)between subgroups were evaluated.A prognostic model was constructed according to prognostic *** analyses in survival,immune infiltration,tumor microenvironment(TME),tumor mutation burden(TMB),stemness,and drug sensitivity between risk groups were *** identified two distinct GM-related subtypes on SKCM and found that GM-related gene alterations were associated with survival probability,clinical features,biological function,and immune *** a risk model based on six DEGs(IL18,SEMA6A,PAEP,TNFRSF17,AIM2,and CXCL10)was constructed and validated for predicting overall survival in SKCM *** results showed that the risk score was negatively correlated with CD8+T cells,activated CD4+memory T cells,M1 macrophages,andγδT *** group with a low-risk score was accompanied by a better survival rate with higher TME scores and lower stemness ***,the group with high-and low-risk score had a significant difference with the sensitivity of 75 drugs(p<0.001).Overall,distinct subtypes in SKCM patients based on GM-related genes were identified and the risk model was constructed,which might contribute to prognosis prediction,guide clinical therapy,and develop novel

关键词： Glutamine metabolism Cutaneous melanoma Immune infiltration Overall survival

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Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolution

arXiv

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arXiv 2024年

作者： Xu, Tianyi Zhou, Yijie Hu, Xiaotao Zhang, Kai Zhang, Anran Qiu, Xingye Xu, Jun School of Statistics and Data Science Nankai University Tianjin China College of Computer Science Nankai University Tianjin China School of Intelligence Science and Technology Nanjing University Suzhou China Tencent Data Platform Beijing China Zhejiang University Hangzhou China Systems Engineering Research Institute China State Shipbuilding Corporation Limited Beijing China Guangdong Provincial Key Laboratory of Big Data Computing The Chinese University of Hong Kong Shenzhen China

Arbitrary-scale super-resolution (ASSR) aims to learn a single model for image super-resolution at arbitrary magnifying scales. Existing ASSR networks typically comprise an off-the-shelf scale-agnostic feature extractor and an arbitrary scale upsampler. These feature extractors often use fixed network architectures to address different ASSR inference tasks, each of which is characterized by an input image and an upsampling scale. However, this overlooks the difficulty variance of super-resolution on different inference scenarios, where simple images or small SR scales could be resolved with less computational effort than difficult images or large SR scales. To tackle this difficulty variability, in this paper, we propose a Task-Aware Dynamic Transformer (TADT) as an input-adaptive feature extractor for efficient image ASSR. Our TADT consists of a multi-scale feature extraction backbone built upon groups of Multi-Scale Transformer Blocks (MSTBs) and a Task-Aware Routing Controller (TARC). The TARC predicts the inference paths within feature extraction backbone, specifically selecting MSTBs based on the input images and SR scales. The prediction of inference path is guided by a new loss function to trade-off the SR accuracy and efficiency. Experiments demonstrate that, when working with three popular arbitrary-scale upsamplers, our TADT achieves state-of-the-art ASSR performance when compared with mainstream feature extractors, but with relatively fewer computational costs. The code will be publicly released. © 2024, CC BY.

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Comparisons of corneal biomechanical and tomographic parameters among thin normal cornea,forme fruste keratoconus,and mild keratoconus

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Eye and Vision 2021年第1期8卷 443-453页

作者： Lei Tian Di Zhang Lili Guo Xiao Qin Hui Zhang Haixia Zhang Ying Jie Lin Li Beijing Institute of Ophthalmology Beijing Tongren Eye CenterBeijing Ophthalmology&Visual Sciences Key LaboratoryBeijing Tongren HospitalCapital Medical UniversityBeijing 100730China Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application Capital Medical UniversityBeijing 100069China School of Biomedical Engineering Capital Medical UniversityBeijing 100069China Beijing Advanced Innovation Center for Big Data‑Based Precision Medicine Beihang University&Capital Medical UniversityBeijing Tongren HospitalBeijing 100730China

Background:To compare the dynamic corneal response(DCR)and tomographic parameters of thin normal cornea(TNC)with thinnest corneal thickness(TCT)(≤500μm),forme fruste keratoconus(FFKC)and mild keratoconus(MKC)had their central corneal thickness(CCT)matched by Scheimpflug imaging(Pentacam)and corneal visualization Scheimpflug technology(Corvis ST).Methods:CCT were matched in 50 eyes with FFKC,50 eyes with MKC,and 53 TNC eyes with TCT≤500μ*** differences in DCR and tomographic parameters among the three groups were *** receiver operating characteristic(ROC)curve was used to analyze the diagnostic significance of these *** propagation(BP)neural network was used to establish the keratoconus diagnosis ***:Fifty CCT-matched FFKC eyes,50 MKC eyes and 50 TNC eyes were *** age and biomechanically corrected intraocular pressure(bIOP)did not differ significantly among the three groups(all P>0.05).The index of height asymmetry(IHA)and height decentration(IHD)differed significantly among the three groups(all P<0.05).IHD also had sufficient strength(area under the ROC curves(AUC)>0.80)to differentiate FFKC and MKC from TNC *** DCR parameters showed significant differences between the MKC and TNC groups,and the deflection amplitude of the first applanation(A1DA)showed a good potential to differentiate(AUC>0.70)FFKC and MKC from TNC *** model by BP neural network showed an accurate diagnostic efficiency of about 91%.Conclusions:The majority of the tomographic and DCR parameters differed among the three *** IHD and partial DCR parameters assessed by Corvis ST distinguished FFKC and MKC from TNC when controlled for CCT.

关键词： Thin normal cornea Forme fruste keratoconus Mild keratoconus Corneal biomechanical parameters

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Detecting Adversarial data by Probing Multiple Perturbations Using Expected Perturbation Score

arXiv

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arXiv 2023年

作者： Zhang, Shuhai Liu, Feng Yang, Jiahao Yang, Yifan Li, Changsheng Han, Bo Tan, Mingkui School of Software Engineering South China University of Technology China Pazhou Laboratory China The University of Melbourne Australia Beijing Institute of Technology Beijing China Department of Computer Science Hong Kong Baptist University Hong Kong Key Laboratory of Big Data and Intelligent Robot Ministry of Education China

Adversarial detection aims to determine whether a given sample is an adversarial one based on the discrepancy between natural and adversarial distributions. Unfortunately, estimating or comparing two data distributions is extremely difficult, especially in high-dimension spaces. Recently, the gradient of log probability density (a.k.a., score) w.r.t. the sample is used as an alternative statistic to compute. However, we find that the score is sensitive in identifying adversarial samples due to insufficient information with one sample only. In this paper, we propose a new statistic called expected perturbation score (EPS), which is essentially the expected score of a sample after various perturbations. Specifically, to obtain adequate information regarding one sample, we perturb it by adding various noises to capture its multi-view observations. We theoretically prove that EPS is a proper statistic to compute the discrepancy between two samples under mild conditions. In practice, we can use a pre-trained diffusion model to estimate EPS for each sample. Last, we propose an EPS-based adversarial detection (EPSAD) method, in which we develop EPS-based maximum mean discrepancy (MMD) as a metric to measure the discrepancy between the test sample and natural samples. We also prove that the EPS-based MMD between natural and adversarial samples is larger than that among natural samples. Extensive experiments show the superior adversarial detection performance of our EPS-AD. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Multi-scale Efficient Graph-Transformer for Whole Slide Image Classification

arXiv

引用

arXiv 2023年

作者： Ding, Saisai Li, Juncheng Wang, Jun Ying, Shihui Shi, Jun The Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University China The Department of Mathematics School of Science Shanghai University China

The multi-scale information among the whole slide images (WSIs) is essential for cancer diagnosis. Although the existing multi-scale vision Transformer has shown its effectiveness for learning multi-scale image representation, it still cannot work well on the gigapixel WSIs due to their extremely large image sizes. To this end, we propose a novel Multi-scale Efficient Graph-Transformer (MEGT) framework for WSI classification. The key idea of MEGT is to adopt two independent Efficient Graph-based Transformer (EGT) branches to process the low-resolution and high-resolution patch embeddings (i.e., tokens in a Transformer) of WSIs, respectively, and then fuse these tokens via a multi-scale feature fusion module (MFFM). Specifically, we design an EGT to efficiently learn the local-global information of patch tokens, which integrates the graph representation into Transformer to capture spatial-related information of WSIs. Meanwhile, we propose a novel MFFM to alleviate the semantic gap among different resolution patches during feature fusion, which creates a non-patch token for each branch as an agent to exchange information with another branch by cross-attention. In addition, to expedite network training, a novel token pruning module is developed in EGT to reduce the redundant tokens. Extensive experiments on TCGA-RCC and CAMELYON16 datasets demonstrate the effectiveness of the proposed MEGT. © 2023, CC BY.

关键词： Image classification

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A Promising Novel Red-Emitting Phorphor Sr3canb2o9: Eu3+ for Near-Uv Excited Wleds

SSRN

引用

SSRN 2022年

作者： Chen, Qian Zhao, Rongli Gong, Xinyong Deng, Chaoyong Zhang, Jun Cui, Ruirui Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang550025 China School of Electronics and Information Engineering Guiyang University Guiyang550005 China College of Computer and Information Engineering Guizhou University of Commerce Guiyang550014 China

A traditional high-temperature solid-phase reaction technique was used to successfully create a series of Sr3CaNb2O9: xEu3+ phosphors with a double perovskite structure. These phosphors' thermal stability and international committee color coordinates have both been carefully examined, along with their microstructure, absorption spectra, and photoluminescence characteristics. The results show that there are no miscellaneous terms in the prepared samples;the microscopic morphology is uniform and full. Under the excitation at 394 nm ( 7F0 → 5L6 ), the emission peaks of the luminous material are most obvious at 593 nm ( 5D0 → 7F1 ) and 611 nm ( 5D0 → 7F2 ). It is noteworthy that the ratio between 611 nm and 593 nm exceeds 1 when the x is greater than 0.2, due to the shift of the main occupancy sites of Eu3+ from the Ca2+ sites with inversion symmetry to the Sr2+ sites, thus providing an environment with inversion asymmetry. Moreover, the optimal doping of Eu3+ is x = 0.30. The concentration quenching mechanism is the closest to the ion interaction. The luminescence intensity percentage of Sr3CaNb2O9: 0.3Eu3+ is 72.5% at 420 K and It's color purity is 98.49%. The aforementioned findings suggest that Sr3CaNb2O9 activated by Eu3+ can be employed as a red light-emitting component for white light-emitting diodes that are driven by near-UV radiation. © 2022, The Authors. All rights reserved.

关键词： Rare earths

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