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A Probabilistic Framework for Temporal Cognitive Diagnosis in Online Learning Systems

Journal of computer science & Technology 2023年第6期38卷 1203-1222页

作者：刘嘉聿汪飞马海平黄振亚刘淇陈恩红苏喻 School of Data Science University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Cognitive Intelligence Hefei 230088China Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of China Hefei 230026China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China School of Computer Science and Artificial Intelligence Hefei Normal UniversityHefei 230061China

Cognitive diagnosis is an important issue of intelligent education systems,which aims to estimate students'proficiency on specific knowledge *** existing studies rely on the assumption of static student states and ig-nore the dynamics of proficiency in the learning process,which makes them unsuitable for online learning *** this paper,we propose a unified temporal item response theory(UTIRT)framework,incorporating temporality and random-ness of proficiency evolving to get both accurate and interpretable diagnosis ***,we hypothesize that stu-dents'proficiency varies as a Wiener process and describe a probabilistic graphical model in UTIRT to consider temporali-ty and randomness ***,based on the relationship between student states and exercising answers,we hy-pothesize that the answering result at time k contributes most to inferring a student's proficiency at time k,which also re-flects the temporality aspect and enables us to get analytical maximization(M-step)in the expectation maximization(EM)algorithm when estimating model *** UTIRT is a framework containing unified training and inferenc-ing methods,and is general to cover several typical traditional models such as Item Response Theory(IRT),multidimen-sional IRT(MIRT),and temporal IRT(TIRT).Extensive experimental results on real-world datasets show the effective-ness of UTIRT and prove its superiority in leveraging temporality theoretically and practically over TIRT.

关键词： cognitive diagnosis probabilistic graphical model item response theory(IRT) stochastic process expectation maximization(EM)algorithm

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BoxCare: A Box Embedding Model for Disease Representation and Diagnosis Prediction in Healthcare data 24

BoxCare: A Box Embedding Model for Disease Representation an...

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33rd Companion of the ACM World Wide Web Conference, WWW 2023

作者： Lv, Hang Chen, Zehai Yang, Yacong Ma, Guofang Tan, Yanchao Yang, Carl College of Computer and Data Science Fuzhou University China School of Computer Science Zhejiang Gongshang University China Department of Computer Science Emory University United States

ISBN: (纸本)9798400701726

Diagnosis prediction is becoming crucial to develop healthcare plans for patients based on Electronic Health Records (EHRs). Existing works usually enhance diagnosis prediction via learning accurate disease representation, where many of them try to capture inclusive relations based on the hierarchical structures of existing disease ontologies such as those provided by ICD-9 codes. However, they overlook exclusive relations that can reflect different and complementary perspectives of the ICD-9 structures, and thus fail to accurately represent relations among diseases and ICD-9 codes. To this end, we propose to project disease embeddings and ICD-9 code embeddings into boxes, where a box is an axis-aligned hyperrectangle with a geometric region and two boxes can clearly "include" or "exclude" each other. Upon box embeddings, we further obtain patient embeddings via aggregating the disease representations for diagnosis prediction. Extensive experiments on two real-world EHR datasets show significant performance gains brought by our proposed framework, yielding average improvements of 6.04% for diagnosis prediction over state-of-the-art competitors. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Diagnosis

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An Improved Honey Badger Algorithm through Fusing Multi-Strategies

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computers, Materials & Continua 2023年第8期76卷 1479-1495页

作者： Zhiwei Ye Tao Zhao Chun Liu Daode Zhang Wanfang Bai School of Computer Science Hubei University of TechnologyWuhan430068China Xining Big Data Service Administration Xining810000China

TheHoney Badger Algorithm(HBA)is a novelmeta-heuristic algorithm proposed recently inspired by the foraging behavior of honey *** dynamic search behavior of honey badgers with sniffing and wandering is divided into exploration and exploitation in HBA,which has been applied in photovoltaic systems and optimization problems ***,HBA tends to suffer from the local optimum and low *** alleviate these challenges,an improved HBA(IHBA)through fusing multi-strategies is presented in the *** introduces Tent chaotic mapping and composite mutation factors to HBA,meanwhile,the random control parameter is improved,moreover,a diversified updating strategy of position is put forward to enhance the advantage between exploration and *** is compared with 7 meta-heuristic algorithms in 10 benchmark functions and 5 engineering *** Wilcoxon Rank-sum Test,Friedman Test and Mann-WhitneyU Test are conducted after *** results indicate the competitiveness and merits of the IHBA,which has better solution quality and convergence *** source code is currently available from:https://***/zhaotao789/IHBA.

关键词： Honey Badger Algorithm multi-strategies fusion tent chaotic mapping compound random factors

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The Implicit Bias of Adam on Separable data 38

The Implicit Bias of Adam on Separable Data

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhang, Chenyang Zou, Difan Cao, Yuan Department of Statistics and Actuarial Science School of Computing and Data Science The University of Hong Kong Hong Kong Department of Computer Science School of Computing and Data Science Institute of Data Science The University of Hong Kong Hong Kong Department of Statistics and Actuarial Science School of Computing and Data Science Department of Mathematics The University of Hong Kong Hong Kong

Adam has become one of the most favored optimizers in deep learning problems. Despite its success in practice, numerous mysteries persist regarding its theoretical understanding. In this paper, we study the implicit bias of Adam in linear logistic regression. Specifically, we show that when the training data are linearly separable, the iterates of Adam converge towards a linear classifier that achieves the maximum ∞-margin in direction. Notably, for a general class of diminishing learning rates, this convergence occurs within polynomial time. Our result shed light on the difference between Adam and (stochastic) gradient descent from a theoretical perspective. © 2024 Neural information processing systems foundation. All rights reserved.

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Distributed Truss Computation in Dynamic Graphs

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Tsinghua science and Technology 2023年第5期28卷 873-887页

作者： Ziwei Mo Qi Luo Dongxiao Yu Hao Sheng Jiguo Yu Xiuzhen Cheng School of Computer Science and Technology Shandong UniversityQingdao 266200China State Key Laboratory of Software Development Environment School of Computer Science and Engineering and the Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China Big Data Institute Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China

Large-scale graphs usually exhibit global sparsity with local cohesiveness,and mining the representative cohesive subgraphs is a fundamental problem in graph *** k-truss is one of the most commonly studied cohesive subgraphs,in which each edge is formed in at least k 2 triangles.A critical issue in mining a k-truss lies in the computation of the trussness of each edge,which is the maximum value of k that an edge can be in a *** works mostly focus on truss computation in static graphs by sequential ***,the graphs are constantly changing dynamically in the real *** study distributed truss computation in dynamic graphs in this *** particular,we compute the trussness of edges based on the local nature of the k-truss in a synchronized node-centric distributed *** decomposing the trussness of edges by relying only on local topological information is possible with the proposed distributed decomposition ***,the distributed maintenance algorithm only needs to update a small amount of dynamic information to complete the *** experiments have been conducted to show the scalability and efficiency of the proposed algorithm.

关键词： distributed algorithm dynamic graph graph mining cohesive subgraph k-truss

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Answering reachability queries with ordered label constraints over labeled graphs

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Frontiers of computer science 2024年第1期18卷 105-117页

作者： Daoliang HE Pingpeng YUAN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science&TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Reachability query plays a vital role in many graph analysis *** researches proposed many methods to efficiently answer reachability queries between vertex *** many real graphs are labeled graph,it highly demands Label-Constrained Reachability(LCR)query inwhich constraint includes a set of labels besides vertex *** researches proposed several methods for answering some LCR queries which require appearance of some labels specified in constraints in the *** that constraint may be a label set,query constraint may be ordered labels,namely OLCR(Ordered-Label-Constrained Reachability)queries which retrieve paths matching a sequence of ***,no solutions are available for ***,we propose DHL,a novel bloom filter based indexing technique for answering OLCR *** can be used to check reachability between vertex *** the answers are not no,then constrained DFS is ***,we employ DHL followed by performing constrained DFS to answer OLCR *** show that DHL has a bounded false positive rate,and it's powerful in saving indexing time and *** experiments on 10 real-life graphs and 12 synthetic graphs demonstrate that DHL achieves about 4.8-22.5 times smaller index space and 4.6-114 times less index construction time than two state-of-art techniques for LCR queries,while achieving comparable query response *** results also show that our algorithm can answer OLCR queries effectively.

关键词： graph ordered-label-constrained reachability partial index bloom filter query processing

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GeoBeeDashboard: An Intelligent Geospatial Platform for Enhancing Waste Management in Tangerang City 13

GeoBeeDashboard: An Intelligent Geospatial Platform for Enha...

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13th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2024

作者： Muljana, Richie Deffansyah, Syauqi Akmal Andrew, Hari Gunawan, Alexander Agung Santoso Irwansyah, Edy Pramudya, Fabian Surya Ario, Muhamad Keenan Syahputra, Muhammad Edo Achmad, Said School of Computer Science Bina Nusantara University Data Science Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Mathematics Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368086

In this study, we created an Intelligent Geospatial Platform called GeoBeeDashboard. The GeoBeeDashboard combines advanced geospatial technologies and artificial intelligence (AI), allowing real-time data visualization and optimized decision-making across multiple sectors. The system architecture consists of a ***-based front end, a FastAPI-driven back end, and PostGIS for geospatial data management. One of the GeoBeeDashboard's primary use cases is addressing waste management issues in Tangerang City, Indonesia. As rapid urbanization increases waste generation, effective management becomes critical. The dashboard identifies critical trends and inefficiencies in Tangerang's districts by K-Means clustering waste management data from 2020 to 2023. Our findings identify distinct clusters, highlighting areas with effective waste management and those that require targeted interventions. The benefits that local government can get from GeoBeeDashboard by utilising insights based on clustering analysis of data per each district in Tangerang to optimise waste collection, allocate resources efficiently, and improve the policy-making process for each district in Tangerang. The GeoBeeDashboard improves local government capabilities by providing a scalable model for other cities facing similar urban challenges. In conclusion, GeoBeeDashboard provides local governments with a powerful tool for addressing waste management inefficiencies and fostering sustainable urban development. © 2024 IEEE.

关键词： Urban planning

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A blockchain-enabled wiki framework based on participatory design

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Digital Communications and Networks 2022年第6期8卷 995-1004页

作者： Zheng Xu Chaofan Liu Peng Zhang Tun Lu Ning Gu School of Computer Science Fudan UniversityShanghaiChina Shanghai Key Laboratory of Data Science Fudan UniversityShanghaiChina

The 5G mobile Internet facilitates contents generation for online communities and platforms through human-to-human ***,a well-known online community,uses wiki technology to build an encyclopedia through collective intelligence and *** wiki systems adopt a centralized implementation,and while existing studies have optimized the efficiency of the wiki systems'centralized implementation,these systems still suffer from a lot of problems,for example,opacity and *** the years,blockchain has brought a flurry of fervour and decentralization to the system architecture,meanwhile giving users a sense of trust and ***,an innovative blockchain-enabled wiki framework called DecWiki is proposed to build one transparent,truthful,collaborative and autonomous *** several participatory design iterations,we present DecWiki's detailed architecture and its implementation in the form of a smart contract and use the interplanetary file system to complement the big data ***,we use the trusted execution environment to secure sensitive information in the wireless ***,the system overhead and the acceptance of the prototype are *** experiments present its significant performance.

关键词： Blockchain Wiki Participatory design Trusted execution envir onment Smart contract

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Retrieval-augmented prompts for text-only image captioning 4

Retrieval-augmented prompts for text-only image captioning

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4th International Conference on computer Graphics, Image, and Virtualization, ICCGIV 2024

作者： Huang, Jinbo Xie, Gang Cao, Li School of Big Data and Computer Science Guizhou Normal University Guiyang550025 China

ISBN: (纸本)9781510683242

Supervised image captioning methods have made significant progress, but high-quality human-annotated image-text paired datasets are costly to collect. Recently, pre-trained vision-language models, such as CLIP, have shown exceptional performance in cross-modal associations, offering novel solutions for image captioning, such as zero-shot captioning through purely textual training. However, the modality gap exists between image and text presents an obstacle to cross-modal alignment within text-only captioning. Moreover, insufficient visual understanding and over-reliance on textual data in training lead to hallucinations (e.g., object misidentification and inaccurate object counts), resulting in irrational captioning. To tackle these issues, this paper presents RAPCap, a text-only method with retrieval-augmented prompts for text-only image captioning. Specifically, RAPCap enhances the language model's understanding of images by incorporating similar captions obtained through retrieval augmentation, thereby alleviating hallucinations. During inference, RAPCap translates the image to textual space to bridge the modality gap. Experimental results demonstrate that RAPCap achieves a new state-of-the-art performance on the Flickr30k and performs competitively on the MS-COCO compared to previous zero-shot captioning. © 2024 SPIE.

关键词： Visual languages

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Real-time distance field acceleration based free-viewpoint video synthesis for large sports fields

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Computational Visual Media 2024年第2期10卷 331-353页

作者： Yanran Dai Jing Li Yuqi Jiang Haidong Qin Bang Liang Shikuan Hong Haozhe Pan Tao Yang School of Telecommunications Engineering Xidian UniversityXi’an 710071China National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology SAIIPthe School of Computer ScienceNorthwestern Polytechnical UniversityXi’an 710129China

Free-viewpoint video allows the user to view objects from any virtual perspective,creating an immersive visual *** technology enhances the interactivity and freedom of multimedia ***,many free-viewpoint video synthesis methods hardly satisfy the requirement to work in real time with high precision,particularly for sports fields having large areas and numerous moving *** address these issues,we propose a freeviewpoint video synthesis method based on distance field *** central idea is to fuse multiview distance field information and use it to adjust the search step size *** step size search is used in two ways:for fast estimation of multiobject three-dimensional surfaces,and synthetic view rendering based on global occlusion *** have implemented our ideas using parallel computing for interactive display,using CUDA and OpenGL frameworks,and have used real-world and simulated experimental datasets for *** results show that the proposed method can render free-viewpoint videos with multiple objects on large sports fields at 25 ***,the visual quality of our synthetic novel viewpoint images exceeds that of state-of-the-art neural-rendering-based methods.

关键词： free-viewpoint video view synthesis camera array distance field sports video

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