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18th ACM International Conference on Web Search and Data Mining, WSDM 2025

作者： Xia, Jiafeng Li, Dongsheng Gu, Hansu Lu, Tun Zhang, Peng Shang, Li Gu, Ning Fudan University Shanghai China Microsoft Research Asia Shanghai China Amazon Seattle United States School of Computer Science Shanghai Key Laboratory of Data Science Fudan University Shanghai China Fudan Institute on Aging MOE Laboratory for National Development and Intelligent Governance Shanghai Institute of Intelligent Electronics & Systems Fudan University Shanghai China

ISBN: (纸本)9798400713293

Sequential recommendation methods can capture dynamic user preferences from user historical interactions to achieve better performance. However, most existing methods only use past information extracted from user historical interactions to train the models, leading to the deviations of user preference modeling. Besides past information, future information is also available during training, which contains the "oracle" user preferences in the future and will be beneficial to model dynamic user preferences. Therefore, we propose an oracle-guided dynamic user preference modeling method for sequential recommendation (Oracle4Rec), which leverages future information to guide model training on past information, aiming to learn "forward-looking" models. Specifically, Oracle4Rec first extracts past and future information through two separate encoders, then learns a forward-looking model through an oracle-guiding module which minimizes the discrepancy between past and future information. We also tailor a two-phase model training strategy to make the guiding more effective. Extensive experiments demonstrate that Oracle4Rec is superior to state-of-the-art sequential methods. Further experiments show that Oracle4Rec can be leveraged as a generic module in other sequential recommendation methods to improve their performance with a considerable margin. © 2025 Copyright held by the owner/author(s).

关键词： dynamic user preference modeling

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Semisupervised Sparse Multilinear Discriminant Analysis

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Journal of Computer Science & Technology 2014年第6期29卷 1058-1071页

作者：黄锴张丽清 MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and EngineeringShanghai Jiao Tong University IEEE

Various problems are encountered when adopting ordinary vector space algorithms for high-order tensor data input. Namely, one must overcome the Small Sample Size （SSS） and overfitting problems. In addition, the structural information of the original tensor signal is lost during the vectorization process. Therefore, comparable methods using a direct tensor input are more appropriate. In the case of electrocardiograms （ECGs）, another problem must be overcome; the manual diagnosis of ECG data is expensive and time consuming, rendering it difficult to acquire data with diagnosis labels. However, when effective features for classification in the original data are very sparse, we propose a semisupervised sparse multilinear discriminant analysis （SSSMDA） method. This method uses the distribution of both the labeled and the unlabeled data together with labels discovered through a label propagation Mgorithm. In practice, we use 12-lead ECGs collected from a remote diagnosis system and apply a short-time-fourier transformation （STFT） to obtain third-order tensors. The experimental results highlight the sparsity of the ECG data and the ability of our method to extract sparse and effective features that can be used for classification.

关键词： ECG analysis semisupervised learning sparse coding dimension reduction tensor learning approach

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On Real Reward Testing

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Journal of Shanghai Jiaotong university(Science) 2011年第4期16卷 479-484页

作者：杨伟忠邓玉欣 MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University

We extend the traditional nonnegative reward testing with negative *** this new testing framework,may preorder and must preorder are the inverse of each *** surprisingly,it turns out that the real reward must testing is no more powerful than the nonnegative reward testing,at least for finite processes. In order to prove that result,we exploit an important property of failure simulation about the inclusion of the testing outcomes between two related processes.

关键词： probabilistic processes real reward testing nonnegative reward testing failure simulation

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Single-cell omics: experimental workflow, data analyses and applications

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Science China(Life Sciences) 2025年第1期68卷 5-102页

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang Xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi Liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi Department of Clinical Laboratory the Affiliated Wuhu Hospital of East China Normal University(The Second People’s Hospital of Wuhu City)Wuhu 241000China Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration(Tongji University) Ministry of EducationOrthopaedic DepartmentTongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji UniversityShanghai 200092China Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Research Institute of Intelligent Computing Zhejiang LabHangzhou 311121China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai 201210China Center for Single-cell Omics School of Public HealthShanghai Jiao Tong University School of MedicineShanghai 200025China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314103China Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China Beijing Institutes of Life Science Chinese Academy of SciencesBeijing 100101China Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary StudiesCenter for Quantitative Biology(CQB)Peking UniversityBeijing 100871China Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women’s HospitalZhejiang University School of MedicineHangzhou 310006China Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of StatisticsEast China Normal U

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular *** exploration of how the genomes orchestrate the formation and maintenance of each cell,and control the cellular phenotypes of various organismsis,is both captivating and *** the inception of the first single-cell RNA technology,technologies related to single-cell sequencing have experienced rapid advancements in recent *** technologies have expanded horizontally to include single-cell genome,epigenome,proteome,and metabolome,while vertically,they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR ***-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases,including ***,we comprehensively summarize recent advances in single-cell omics technologies,with a specific focus on the methodology *** overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

关键词： single-cell sequencing genome epigenome proteomics metabolomics multimodal spatial transcriptomics CRISPR screening

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How faithfully can π be interpreted in SA?

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Science China(Information Sciences) 2013年第3期56卷 82-96页

作者： LONG Huan FU YuXi Basic Studies in Computing Science Department of Computer ScienceMOE-MS Key Laboratory for Intelligent Computing and Intelligent SystemsShanghai Jiao Tong University

The π calculus and the safe ambient calculus are two of the widely studied variants of process calculi in the field of concurrency *** former is the most classic model for mobile processes and the latter is well known for its nested ***,the relationship between these two models deserves further *** this paper,we reinvestigate this problem *** first give the strengthened encoding *** we propose the encoding of the synchronous π-calculus into the safe ambients *** encoding scheme is a generalization and improvement of Levi and Sangiorgi’s work when moving from the asynchronous π-calculus to the synchronous π-*** show the merits of the encoding by checking the mentioned criteria.

关键词： encoding expressiveness synchronous π-calculus safe ambients

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An interpretation of Erlang into value-passing calculus

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Journal of Networks 2013年第7期8卷 1504-1513页

作者： Huang, Hao Yang, Fei Department of Computer Science Shanghai Jiaotong University MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems China

In this paper we present a new process calculus VPCΣ and an interpretation for core Erlang. VPCΣ is at least as expressive as VPC and it is more effective for verification with some built-in functions. The wellestablished symbolic bisimulation in value-passing calculus is now helpful for solving the infinite-state space problem of data values in equivalence checking and verfication. Compared to the previous formalization work of modeling core Erlang in π-calculus, the new interpretation has the following main merits: some essential features for Erlang are implemented faithfully;and above all the soundness of the interpretation is proved with respect to late symbolic bisimulation. © 2013 ACADEMY PUBLISHER.

关键词： Calculations

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Process Passing Calculus,Revisited

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Journal of Shanghai Jiaotong university(Science) 2013年第1期18卷 29-36页

作者：尹强龙环 Laboratory of Basic Study in Computing Science MOE-MS Key Laboratory for Intelligent Computing and Intelligent SystemsDepartment of Computer Science and EngineeringShanghai Jiaotong University

In the context of process calculi, higher order π calculus （A calculus） is prominent and popular due to its ability to transfer processes. Motivated by the attempt to study the process theory in an integrated way, we give a system study of A calculus with respect to the model independent framework. We show the coincidence of the context bisimulation to the absolute equality. We also build a subbisimilarity relation from A calculus to the π calculus.

关键词： higher order π-calculus encoding expressiveness bisimulation

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Edgel index for large-scale sketch-based image search

Edgel index for large-scale sketch-based image search

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作者： Cao, Yang Wang, Changhu Zhang, Liqing Zhang, Lei MOE Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University China Microsoft Research Asia Beijing China

ISBN: (纸本)9781457703942

Retrieving images to match with a hand-drawn sketch query is a highly desired feature, especially with the popularity of devices with touch screens. Although query-by-sketch has been extensively studied since 1990s, it is still very challenging to build a real-time sketch-based image search engine on a large-scale database due to the lack of effective and efficient matching/indexing solutions. The explosive growth of web images and the phenomenal success of search techniques have encouraged us to revisit this problem and target at solving the problem of web-scale sketch-based image retrieval. In this work, a novel index structure and the corresponding raw contour-based matching algorithm are proposed to calculate the similarity between a sketch query and natural images, and make sketch-based image retrieval scalable to millions of images. The proposed solution simultaneously considers storage cost, retrieval accuracy, and efficiency, based on which we have developed a real-time sketch-based image search engine by indexing more than 2 million images. Extensive experiments on various retrieval tasks (basic shape search, specific image search, and similar image search) show better accuracy and efficiency than state-of-the-art methods. © 2011 IEEE.

关键词： Efficiency

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Motion deblurring using super-sparsity

Motion deblurring using super-sparsity

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Zhao, Jingxiong Zhao, Haohua Zhang, Keting Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9783642420504

Motion blur is caused by the camera shake during the exposure in which the blur kernel describes the trace of shaking. Based on this generating process of the kernel , we observed that the distribution of the kernel obeys super-sparsity, as the natural images. Recent works mostly exploit various kinds of priors in their models, but focus on the the speed or a close-form formulation for convenience of mathematical calculation ignoring the intrinsic feature of the kernels and images. In this paper we propose a new model with super-sparse prior for the deblurring problem from one single image. Since the close-form formulation of this model doesn't exist, we use a look-up table trick to approximate the solution. Qualitative and quantitative evaluation demonstrate that our model with super-sparse prior can produce stable and high-quality results. © Springer-Verlag 2013.

关键词： Convolution

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A robust human action recognition system using single camera

A robust human action recognition system using single camera

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2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

作者： Yuan, Xin Yang, Xubo MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems School of Software Shanghai Jiao Tong University China

ISBN: (纸本)9781424445073

This paper describes a system for action recognition with a single camera. Firstly, we use a two-layered background subtraction, which is based on both chromaticity and gradient, to extract human contours from the frame sequence captured by camera. This subtraction helps us remove shadows from foreground and get a good contour for recognition. Then we parameterize a human posture with a model called star skeleton. Each posture is represented as five vectors by this model. To classify every posture into a symbol, we trained a classifier by SVM with a set of exemplars. This classifier calculates a symbol according to the star skeleton. So it transfers the frame sequence into a symbol sequence. Finally, an action is recognized from the symbol sequence with a string matching. Our system can be regarded as a new way for interaction between human and computer. It achieves a high and stable recognition rate in complex environment, and the experimental results show the promising effectiveness. ©2009 IEEE.

关键词： Stars

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