Data4UrbanMobility was presented on the 20th November 2018 during the Leibniz Startup & Industry Event Artificial Intelligence. The PROJEKTIONISTEN® GmbH together with the Research Center L3S explained current project outcomes like the D4UM-App and the Dashboard to interested visitors.

We very much enjoyed the interesting discussion and are very happy about all participants in our Citizen Science App “MiC – Move in the City”.

• SM4Depth: Seamless Monocular Metric Depth Estimation across Multiple Cameras and Scenes by One Model. Liu, Yihao; Xue, Feng; Ming, Anlong; Zhao, Mingshuai; Ma, Huadong; Sebe, Nicu J. Cai, M. S. Kankanhalli, B. Prabhakaran, S. Boll, R. Subramanian, L. Zheng, V. K. Singh, P. César, L. Xie, D. Xu (eds.) (2024). 3469–3478.
• A Novel Dynamic Hybrid Beamforming Design for ELAA Systems. Liu, Mengzhen; Li, Ming; Liu, Rang; Liu, Qian (2024). 4494–4499.
• Generating Multiple Choice Questions from Scientific Literature via Large Language Models. Luo, Shunyang; Tang, Yuqi; Jiang, Mingyuan; Feng, Kehua; Zhang, Qiang; Ding, Keyan V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 219–226.
• Enhancing Risk Assessment in Transformers with Loss-at-Risk Functions. Zhang, Jinghan; Xie, Henry; Zhang, Xinhao; Liu, Kunpeng V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 477–484.
• Instance-Level Neural Feature Selection Based on Disentanglement Enhancement. Liu, Zihao; Pan, Jun; Wang, Hao; Yu, Kui V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 211–218.
• Knowledge Graph Reasoning with Logics and Embeddings: Survey and Perspective. Zhang, Wen; Chen, Jiaoyan; Li, Juan; Xu, Zezhong; Pan, Jeff Z.; Chen, Huajun V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 492–499.
• Deep Learning for SLP-based ISAC Waveform Design. Jiang, Peng; Liu, Rang; Li, Ming; Xiao, Zichao; Liu, Qian (2024). 2270–2275.
• MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images. Li, Xurui; Huang, Ziming; Xue, Feng; Zhou, Yu (2024).
• Generating High-Quality Symbolic Music Using Fine-Grained Discriminators. Zhang, Zhedong; Li, Liang; Zhang, Jiehua; Hu, Zhenghui; Wang, Hongkui; Yan, Chenggang; Yang, Jian; Qi, Yuankai in Lecture Notes in Computer Science, A. Antonacopoulos, S. Chaudhuri, R. Chellappa, C.-L. Liu, S. Bhattacharya, U. Pal (eds.) (2024). (Vol. 15320) 332–344.
• Distortion-Aware Beamforming Design for MU-MISO Systems. Liu, Mengzhen; Li, Ming; Liu, Rang; Liu, Qian (2024). 1–5.
• Active RIS Empowered Secure MISO Systems: AN and RIF Approaches. Yu, Ming; Chu, Jinjin; Liu, Rang; Li, Peishi; Li, Ming; Liu, Qian (2024). 1–5.
• RIS-based Dual-Functional Access Point for Energy Efficiency in Cell-Free Systems. Lu, Manwei; Yu, Ming; Liu, Rang; Liu, Sifan; Li, Ming; Wang, Wei; Liu, Qian (2024). 1–5.
• Model-Driven Deep Learning for Joint Waveform and Beamforming Design in RIS-ISAC Systems. Jiang, Peng; Liu, Rang; Li, Ming; Wang, Wei; Liu, Qian (2024). 1–5.
• MedIE-Instruct: A Comprehensive Instruction Dataset for Medical Information Extraction. Xiang, Zhuoyi; Wang, Xinda; Yan, Xiaodong; Zhao, Deng; Ding, Keyan; Zhang, Qiang V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 420–427.
• Bias Reduced Semidefinite Relaxation Method for Multistatic Localization in the Absence of Transmitter Position And Its Synchronization. Pei, Jian; Wang, Gang; Ho, K. C.; Huang, Lei (2023). 1–5.
• A Quantize-then-Estimate Protocol for CSI Acquisition in IRS-Aided Downlink Communication. Wang, Rui; Wang, Zhaorui; Liu, Liang; Zhang, Shuowen; Jin, Shi (2023). 6127–6132.
• Uncertainty-Aware Image Captioning. Fei, Zhengcong; Fan, Mingyuan; Zhu, Li; Huang, Junshi; Wei, Xiaoming; Wei, Xiaolin B. Williams, Y. Chen, J. Neville (eds.) (2023). 614–622.
• Masked Auto-Encoders Meet Generative Adversarial Networks and Beyond. Fei, Zhengcong; Fan, Mingyuan; Zhu, Li; Huang, Junshi; Wei, Xiaoming; Wei, Xiaolin (2023). 24449–24459.
• Pyramid Ensemble Structure for High Resolution Image Shadow Removal. Cui, Shuhao; Huang, Junshi; Tian, Shuman; Fan, Mingyuan; Zhang, Jiaqi; Zhu, Li; Wei, Xiaoming; Wei, Xiaolin (2023). 1311–1319.
• Terrain Classification Using Inside-Wheel Cameras Based on Wheel-Terrain Interaction Characteristics. Hu, Longteng; Xue, Feng; Yao, Chen; Li, Yunzhou; Wei, Jin; Wang, Peichen; Zhu, Zheng; Jia, Zhenzhong (2023). 1–6.
• Terrain Classification Based on Wheel-terrain Interaction Measurements using Aside-Wheel Camera. Xue, Feng; Hu, Longteng; Yao, Chen; Wei, Jin; Li, Yunzhou; Wang, Peichen; Zhu, Zheng; Jia, Zhenzhong (2023). 1–6.
• Multimodal Counterfactual Learning Network for Multimedia-based Recommendation. Li, Shuaiyang; Guo, Dan; Liu, Kang; Hong, Richang; Xue, Feng H.-H. Chen, W.-J. (Edward) Duh, H.-H. Huang, M. P. Kato, J. Mothe, B. Poblete (eds.) (2023). 1539–1548.
• Unknown Sniffer for Object Detection: Don’t Turn a Blind Eye to Unknown Objects. Liang, Wenteng; Xue, Feng; Liu, Yihao; Zhong, Guofeng; Ming, Anlong (2023). 3230–3239.
• Feature Selection and Extreme Learning Machine Tuning by Hybrid Sand Cat Optimization Algorithm for Diabetes Classification. Stankovic, Marko; Bacanin, Nebojsa; Zivkovic, Miodrag; Jovanovic, Dijana; Antonijevic, Milos; Bukmira, Milos; Strumberger, Ivana in Communications in Computer and Information Science, D. Simian, L. F. Stoica (eds.) (2022). (Vol. 1761) 188–203.
• Multivariate Time Series Anomaly Detection with Few Positive Samples. Xue, Feng; Yan, Weizhong (2022). 1–7.
• Social engineering: how crowdmasters, phreaks, hackers, and trolls created a new form of manipulative communication Gehl, Robert W.; Lawson, Sean T. (2022). Cambridge, The MIT Press.

  Manipulative communication—from early twentieth-century propaganda to today's online con artistry—examined through the lens of social engineering. The United States is awash in manipulated information about everything from election results to the effectiveness of medical treatments. Corporate social media is an especially good channel for manipulative communication, with Facebook a particularly willing vehicle for it. In Social Engineering, Robert Gehl and Sean Lawson show that online misinformation has its roots in earlier techniques: mass social engineering of the early twentieth century and interpersonal hacker social engineering of the 1970s, converging today into what they call “masspersonal social engineering.” As Gehl and Lawson trace contemporary manipulative communication back to earlier forms of social engineering, possibilities for amelioration become clearer. The authors show how specific manipulative communication practices are a mixture of information gathering, deception, and truth-indifferent statements, all with the instrumental goal of getting people to take actions the social engineer wants them to. Yet the term “fake news,” they claim, reduces everything to a true/false binary that fails to encompass the complexity of manipulative communication or to map onto many of its practices. They pay special attention to concepts and terms used by hacker social engineers, including the hacker concept of “bullshitting,” which the authors describe as a truth-indifferent mix of deception, accuracy, and sociability. They conclude with recommendations for how society can undermine masspersonal social engineering and move toward healthier democratic deliberation.
• Monocular Depth Distribution Alignment with Low Computation. Sheng, Fei; Xue, Feng; Chang, Yicong; Liang, Wenteng; Ming, Anlong (2022). 6548–6555.
• Fast Road Segmentation via Uncertainty-aware Symmetric Network. Chang, Yicong; Xue, Feng; Sheng, Fei; Liang, Wenteng; Ming, Anlong (2022). 11124–11130.
• Analysis of Robot Traversability over Unstructured Terrain using Information Fusion. Zhang, Wenyao; Lyu, Shipeng; Yao, Chen; Xue, Feng; Zhu, Zheng; Jia, Zhenzhong (2022). 413–418.
• Sound-Based Terrain Classification for Multi-modal Wheel-Leg Robots. Xue, Feng; Hu, Longteng; Yao, Chen; Liu, Zhengtao; Zhu, Zheng; Jia, Zhenzhong (2022). 174–179.
• Fault Diagnosis of Microgrids Using Branch Convolution Neural Network and Majority Voting. Li, Zhoubing; Zhang, Meng; Li, Lin; Guan, Xiaohong (2022). 328–333.
• Intelligent Visualization System for Big Multi-source Medical Data Based on Data Lake. Ren, Peng; Mao, Ziyun; Li, Shuaibo; Xiao, Yang; Ke, Yating; Yao, Lanyu; Lan, Hao; Li, Xin; Sheng, Ming; Zhang, Yong in Lecture Notes in Computer Science, C. Xing, X. Fu, Y. Zhang, G. Zhang, C. Borjigin (eds.) (2021). (Vol. 12999) 706–717.
• Learning Associations between Features and Clusters: An Interpretable Deep Clustering Method. Huang, Hao; Xue, Feng; Yan, Weizhong; Wang, Tianyi; Yoo, Shinjae; Xu, Chenxiao (2021). 1–10.
• MHDP: An Efficient Data Lake Platform for Medical Multi-source Heterogeneous Data. Ren, Peng; Li, Shuaibo; Hou, Wei; Zheng, Wenkui; Li, Zhen; Cui, Qin; Chang, Wang; Li, Xin; Zeng, Chun; Sheng, Ming; Zhang, Yong in Lecture Notes in Computer Science, C. Xing, X. Fu, Y. Zhang, G. Zhang, C. Borjigin (eds.) (2021). (Vol. 12999) 727–738.
• Morphable Detector for Object Detection on Demand. Zhao, Xiangyun; Zou, Xu; Wu, Ying (2021). 4751–4760.
• Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis. He, Yutong; Wang, Dingjie; Lai, Nicholas; Zhang, William; Meng, Chenlin; Burke, Marshall; Lobell, David B.; Ermon, Stefano M. Ranzato, A. Beygelzimer, Y. N. Dauphin, P. Liang, J. W. Vaughan (eds.) (2021). 27903–27915.
• Graph Attention-Based Deep Neural Network for 3D Point Cloud Processing. Li, Xun; Xue, Feng; Chen, Chao; Yuan, Xiaohui; Lu, Qiang (2021). 1–6.
• HMDFF: A Heterogeneous Medical Data Fusion Framework Supporting Multimodal Query. Ren, Peng; Lin, Weihang; Liang, Ye; Wang, Ruoyu; Liu, Xingyue; Zuo, Baifu; Chen, Tan; Li, Xin; Sheng, Ming; Zhang, Yong in Lecture Notes in Computer Science, S. Siuly, H. Wang, L. Chen, Y. Guo, C. Xing (eds.) (2021). (Vol. 13079) 254–266.
• Multi-stage Knowledge Propagation Network for Recommendation. Xue, Feng; Zhou, Wenjie; Hong, Zikun; Liu, Kang in Communications in Computer and Information Science, B. Qin, Z. Jin, H. Wang, J. Z. Pan, Y. Liu, B. An (eds.) (2021). (Vol. 1466) 253–264.
• Flight data anomaly detection and diagnosis with variable association change. He, Sijie; Huang, Hao; Yoo, Shinjae; Yan, Weizhong; Xue, Feng; Wang, Tianyi; Xu, Chenxiao C.-C. Hung, J. Hong, A. Bechini, E. Song (eds.) (2021). 346–354.
• On The Degrees Of Freedom in Total Variation Minimization. Xue, Feng; Blu, Thierry (2020). 5690–5694.
• Imbalanced Time Series Classification for Flight Data Analyzing with Nonlinear Granger Causality Learning. Huang, Hao; Xu, Chenxiao; Yoo, Shinjae; Yan, Weizhong; Wang, Tianyi; Xue, Feng M. d’Aquin, S. Dietze, C. Hauff, E. Curry, P. Cudré-Mauroux (eds.) (2020). 2533–2540.
• A Novel Multi-layer Framework for Tiny Obstacle Discovery. Xue, Feng; Ming, Anlong; Zhou, Menghan; Zhou, Yu (2019). 2939–2945.
• Generative Creativity: Adversarial Learning for Bionic Design. Yu, Simiao; Dong, Hao; Wang, Pan; Wu, Chao; Guo, Yike in Lecture Notes in Computer Science, I. V. Tetko, V. Kurková, P. Karpov, F. J. Theis (eds.) (2019). (Vol. 11729) 525–536.
• Discriminative and Correlative Partial Multi-Label Learning. Wang, Haobo; Liu, Weiwei; Zhao, Yang; Zhang, Chen; Hu, Tianlei; Chen, Gang S. Kraus (ed.) (2019). 3691–3697.
• Mining Graphs and Networks: A 15-Year Journey. Pei, Jian in CEUR Workshop Proceedings, A. Bifet, M. Berlingerio, J. Gama, J. Read, A. R. Nogueira (eds.) (2019). (Vol. 2579)
• Occlusion-Shared and Feature-Separated Network for Occlusion Relationship Reasoning. Lu, Rui; Xue, Feng; Zhou, Menghan; Ming, Anlong; Zhou, Yu (2019). 10342–10351.
• An Iterative Sure-Let Deconvolution Algorithm Based on BM3D Denoiser. Xue, Feng; Li, Jizhou; Blu, Thierry (2019). 1795–1799.
• Visual-SLIM: Integrated Sparse Linear Model with Visual Features for Personalized Recommendation. Chen, Siyang; Xue, Feng; Zhang, Haobo in Lecture Notes in Computer Science, R. Hong, W.-H. Cheng, T. Yamasaki, M. Wang, C.-W. Ngo (eds.) (2018). (Vol. 11164) 126–135.
• Accurate 3D PSF estimation from a wide-field microscopy image. Li, Jizhou; Xue, Feng; Blu, Thierry (2018). 501–504.
• How to Exploit Weaknesses in Biomedical Challenge Design and Organization. Reinke, Annika; Eisenmann, Matthias; Onogur, Sinan; Stankovic, Marko; Scholz, Patrick; Full, Peter M.; Bogunovic, Hrvoje; Landman, Bennett A.; Maier, Oskar; Menze, Bjoern H.; Sharp, Gregory C.; Sirinukunwattana, Korsuk; Speidel, Stefanie; van der Sommen, Fons; Zheng, Guoyan; Müller, Henning; Kozubek, Michal; Arbel, Tal; Bradley, Andrew P.; Jannin, Pierre; Kopp-Schneider, Annette; Maier-Hein, Lena in Lecture Notes in Computer Science, A. F. Frangi, J. A. Schnabel, C. Davatzikos, C. Alberola-López, G. Fichtinger (eds.) (2018). (Vol. 11073) 388–395.
• Recursive Evaluation of Sure for Total Variation Denoising. Xue, Feng; Blu, Thierry; Liu, Jiaqi; Ai, Xia (2018). 1338–1342.
• Security-Driven Task Scheduling for Multiprocessor System-on-Chips with Performance Constraints. Wang, Nan; Yao, Manting; Jiang, Dongxu; Chen, Song; Zhu, Yu (2018). 545–550.
• A Novel Gcv-Based Criterion for Parameter Selection In Image Deconvolution. Xue, Feng; Blu, Thierry; Liu, Jiaqi; Ai, Xia (2018). 1403–1407.
• Abstract: Können wir Rankings vertrauen? Eine systematische Analyse biomedizinischer Challenges hinsichtlich Reporting und Design. Eisenmann, Matthias; Scholz, Patrick; Stankovic, Marko; Jannin, Pierre; Stock, Christian; Maier-Hein, Lena in Informatik Aktuell, K. H. Maier-Hein, T. M. Deserno, H. Handels, T. Tolxdorff (eds.) (2017). 49.
• Gaussian blur estimation for photon-limited images. Li, Jizhou; Xue, Feng; Blu, Thierry (2017). 495–499.
• An iterative sure-let approach to sparse reconstruction. Xue, Feng; Blu, Thierry; Du, Runle; Liu, Jiaqi (2016). 4493–4497.
• Modelling Sentence Pairs with Tree-structured Attentive Encoder. Zhou, Yao; Liu, Cong; Pan, Yan N. Calzolari, Y. Matsumoto, R. Prasad (eds.) (2016). 2912–2922.
• A Localized Efficient Forwarding Algorithm in Large-Scale Delay Tolerant Networks. He, Yuxing; Liu, Cong; Pan, Yan; Zhang, Jun; Wu, Jie; Zhao, Yaxiong; Yang, Shuhui; Lu, Mingming (2014). 594–599.
• Sonic Hedgehog Signaling Inhibition Provides Opportunities for Targeted Therapy by Sulforaphane in Regulating Pancreatic Cancer Stem Cell Self-Renewal. Rodova, Mariana; Fu, Junsheng; Watkins, Dara Nall; Srivastava, Rakesh K.; Shankar, Sharmila (2012). 7(9) 1–10.

  Dysregulation of the sonic hedgehog (Shh) signaling pathway has been associated with cancer stem cells (CSC) and implicated in the initiation of pancreatic cancer. Pancreatic CSCs are rare tumor cells characterized by their ability to self-renew, and are responsible for tumor recurrence accompanied by resistance to current therapies. The lethality of these incurable, aggressive and invasive pancreatic tumors remains a daunting clinical challenge. Thus, the objective of this study was to investigate the role of Shh pathway in pancreatic cancer and to examine the molecular mechanisms by which sulforaphane (SFN), an active compound in cruciferous vegetables, inhibits self-renewal capacity of human pancreatic CSCs. Interestingly, we demonstrate here that Shh pathway is highly activated in pancreatic CSCs and plays important role in maintaining stemness by regulating the expression of stemness genes. Given the requirement for Hedgehog in pancreatic cancer, we investigated whether hedgehog blockade by SFN could target the stem cell population in pancreatic cancer. In an in vitro model, human pancreatic CSCs derived spheres were significantly inhibited on treatment with SFN, suggesting the clonogenic depletion of the CSCs. Interestingly, SFN inhibited the components of Shh pathway and Gli transcriptional activity. Interference of Shh-Gli signaling significantly blocked SFN-induced inhibitory effects demonstrating the requirement of an active pathway for the growth of pancreatic CSCs. SFN also inhibited downstream targets of Gli transcription by suppressing the expression of pluripotency maintaining factors (Nanog and Oct-4) as well as PDGFRα and Cyclin D1. Furthermore, SFN induced apoptosis by inhibition of BCL-2 and activation of caspases. Our data reveal the essential role of Shh-Gli signaling in controlling the characteristics of pancreatic CSCs. We propose that pancreatic cancer preventative effects of SFN may result from inhibition of the Shh pathway. Thus Sulforaphane potentially represents an inexpensive, safe and effective alternative for the management of pancreatic cancer.
• A compact integrated 100 GS/s sampling module for UWB see through wall radar with fast refresh rate for dynamic real time imaging. Liu, Quanhua; Wang, Yazhou; Fathy, Aly E. (2012). 59–62.
• Sure-based blind Gaussian deconvolution. Xue, Feng; Blu, Thierry (2012). 452–455.
• SURE-LET image deconvolution using multiple Wiener filters. Xue, Feng; Luisier, Florian; Blu, Thierry (2012). 3037–3040.
• Suggesting Topic-Based Query Terms as You Type. Fan, Ju; Wu, Hao; Li, Guoliang; Zhou, Lizhu W.-S. Han, D. Srivastava, G. Yu, H. Yu, Z. H. Huang (eds.) (2010). 61–67.
• Firefly: illuminating future network-on-chip with nanophotonics. Pan, Yan; Kumar, Prabhat; Kim, John; Memik, Gokhan; Zhang, Yu; Choudhary, Alok N. S. W. Keckler, L. A. Barroso (eds.) (2009). 429–440.
• Jet engine gas path fault diagnosis using dynamic fusion of multiple classifiers. Yan, Weizhong; Xue, Feng (2008). 1585–1591.
• Privacy-Preserving Data Stream Classification. Xu, Yabo; Wang, Ke; Fu, Ada Wai-Chee; She, Rong; Pei, Jian C. C. Aggarwal, P. S. Yu (eds.) (2008). (Vol. 34) 487–510.
• A Survey of Utility-based Privacy-Preserving Data Transformation Methods. Hua, Ming; Pei, Jian C. C. Aggarwal, P. S. Yu (eds.) (2008). (Vol. 34) 207–237.
• Temperature Control in Precalcinator with Dual Heuristic Dynamic Programming. Lin, Xiaofeng; Zhang, Zhigang; Liu, Derong (2007). 344–349.
• Efficiently Answering Top-k Typicality Queries on Large Databases. Hua, Ming; Pei, Jian; Fu, Ada Wai-Chee; Lin, Xuemin; fung Leung, Ho C. Koch, J. Gehrke, M. N. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, D. Florescu, C. Y. Chan, V. Ganti, C.-C. Kanne, W. Klas, E. J. Neuhold (eds.) (2007). 890–901.
• Minimality Attack in Privacy Preserving Data Publishing. Wong, Raymond Chi-Wing; Fu, Ada Wai-Chee; Wang, Ke; Pei, Jian C. Koch, J. Gehrke, M. N. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, D. Florescu, C. Y. Chan, V. Ganti, C.-C. Kanne, W. Klas, E. J. Neuhold (eds.) (2007). 543–554.
• A Review of Two Industrial Deployments of Multi-criteria Decision-making Systems at General Electric. Subbu, Raj; Bonissone, Piero P.; Bollapragada, Srinivas; Chalermkraivuth, Kete Charles; Eklund, Neil H. W.; Iyer, Naresh; Shah, Rasik; Xue, Feng; Yan, Weizhong (2007). 136–145.
• Probabilistic Skylines on Uncertain Data. Pei, Jian; Jiang, Bin; Lin, Xuemin; Yuan, Yidong C. Koch, J. Gehrke, M. N. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, D. Florescu, C. Y. Chan, V. Ganti, C.-C. Kanne, W. Klas, E. J. Neuhold (eds.) (2007). 15–26.
• Multi-Dimensional Analysis of Data Streams Using Stream Cubes. Han, Jiawei; Cai, Yandong; Chen, Yixin; Dong, Guozhu; Pei, Jian; Wah, Benjamin W.; Wang, Jianyong C. C. Aggarwal (ed.) (2007). (Vol. 31) 103–125.
• Parametric model-based anomaly detection for locomotive subsystems. Xue, Feng; Yan, Weizhong (2007). 3074–3079.
• Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures. Li, Jiuyong; Wong, Raymond Chi-Wing; Fu, Ada Wai-Chee; Pei, Jian in Lecture Notes in Computer Science, A. M. Tjoa, J. Trujillo (eds.) (2006). (Vol. 4081) 405–416.
• Using High Dimensional Indexes to Support Relevance Feedback Based Interactive Images Retrival. Zhang, Junqi; Zhou, Xiangdong; Wang, Wei; Shi, Baile; Pei, Jian U. Dayal, K.-Y. Whang, D. B. Lomet, G. Alonso, G. M. Lohman, M. L. Kersten, S. K. Cha, Y.-K. Kim (eds.) (2006). 1211–1214.
• Minimum Description Length Principle: Generators Are Preferable to Closed Patterns. Li, Jinyan; Li, Haiquan; Wong, Limsoon; Pei, Jian; Dong, Guozhu (2006). 409–414.
• Efficiently Mining Frequent Closed Partial Orders. Pei, Jian; Liu, Jian; Wang, Haixun; Wang, Ke; Yu, Philip S.; Wang, Jianyong (2005). 753–756.
• Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces. Pei, Jian; Jin, Wen; Ester, Martin; Tao, Yufei K. Böhm, C. S. Jensen, L. M. Haas, M. L. Kersten, P.- Åke Larson, B. C. Ooi (eds.) (2005). 253–264.
• Mining Most General Multidimensional Summarization of Probably Groups in Data Warehouses. Yu, Hui; Pei, Jian; Tang, Shiwei; Yang, Dongqing J. Frew (ed.) (2005). 185–194.
• GraphMiner: a structural pattern-mining system for large disk-based graph databases and its applications. Wang, Wei; Wang, Chen; Zhu, Yongtai; Shi, Baile; Pei, Jian; Yan, Xifeng; Han, Jiawei F. Özcan (ed.) (2005). 879–881.
• Data Mining: The Next Generation. Ramakrishnan, Raghu; Agrawal, Rakesh; Freytag, Johann-Christoph; Bollinger, Toni; Clifton, Christopher W.; Dzeroski, Saso; Hipp, Jochen; Keim, Daniel A.; Kramer, Stefan; Kriegel, Hans-Peter; Leser, Ulf; Liu, Bing; Mannila, Heikki; Meo, Rosa; Morishita, Shinichi; Ng, Raymond T.; Pei, Jian; Raghavan, Prabhakar; Spiliopoulou, Myra; Srivastava, Jaideep; Torra, Vicenç in Dagstuhl Seminar Proceedings, R. Agrawal, J.-C. Freytag, R. Ramakrishnan (eds.) (2004). (Vol. 04292)
• Preface to CoMWIM 2004. Yang, Dongqing; Tang, Shiwei; Pei, Jian; Wang, Tengjiao; Gao, Jun in Lecture Notes in Computer Science, S. Wang, D. Yang, K. Tanaka, F. Grandi, S. Zhou, E. E. Mangina, T. W. Ling, I.-Y. Song, J. Guan, H. C. Mayr (eds.) (2004). (Vol. 3289) 197.
• Data Mining for Intrusion Detection: Techniques, Applications and Systems. Pei, Jian; Upadhyaya, Shambhu J.; Farooq, Faisal; Govindaraju, Venugopal Z. M. Özsoyoglu, S. B. Zdonik (eds.) (2004). 877.
• A Fast Algorithm for Subspace Clustering by Pattern Similarity. Wang, Haixun; Chu, Fang; Fan, Wei; Yu, Philip S.; Pei, Jian (2004). 51–60.
• Mining Confident Colocation Rules without A Support Threshold. Huang, Yan; Xiong, Hui; Shekhar, Shashi; Pei, Jian G. B. Lamont, H. Haddad, G. A. Papadopoulos, B. Panda (eds.) (2003). 497–501.
• SOCQET: Semantic OLAP with Compressed Cube and Summarization. Lakshmanan, Laks V. S.; Pei, Jian; Zhao, Yan A. Y. Halevy, Z. G. Ives, A. Doan (eds.) (2003). 658.
• ApproxMAP: Approximate Mining of Consensus Sequential Patterns. Kum, Hye-Chung; Pei, Jian; Wang, Wei; Duncan, Dean D. Barbará, C. Kamath (eds.) (2003). 311–315.
• MaPle: A Fast Algorithm for Maximal Pattern-based Clustering. Pei, Jian; Zhang, Xiaoling; Cho, Moonjung; Wang, Haixun; Yu, Philip S. (2003). 259–266.
• QC-Trees: An Efficient Summary Structure for Semantic OLAP. Lakshmanan, Laks V. S.; Pei, Jian; Zhao, Yan A. Y. Halevy, Z. G. Ives, A. Doan (eds.) (2003). 64–75.
• Online Analytical Processing Stream Data: Is It Feasible?. Chen, Yixin; Dong, Guozhu; Han, Jiawei; Pei, Jian; Wah, Benjamin W.; Wang, Jianyong (2002).
• On Computing Condensed Frequent Pattern Bases. Pei, Jian; Dong, Guozhu; Zou, Wei; Han, Jiawei (2002). 378–385.
• Quotient Cube: How to Summarize the Semantics of a Data Cube. Lakshmanan, Laks V. S.; Pei, Jian; Han, Jiawei (2002). 778–789.
• Fault-Tolerant Frequent Pattern Mining: Problems and Challenges. Pei, Jian; Tung, Anthony K. H.; Han, Jiawei (2001).
• Mining Multi-Dimensional Constrained Gradients in Data Cubes. Dong, Guozhu; Han, Jiawei; Lam, Joyce M. W.; Pei, Jian; Wang, Ke P. M. G. Apers, P. Atzeni, S. Ceri, S. Paraboschi, K. Ramamohanarao, R. T. Snodgrass (eds.) (2001). 321–330.
• Multi-Dimensional Sequential Pattern Mining. Pinto, Helen; Han, Jiawei; Pei, Jian; Wang, Ke; Chen, Qiming; Dayal, Umeshwar (2001). 81–88.
• PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth. Pei, Jian; Han, Jiawei; Mortazavi-Asl, Behzad; Pinto, Helen; Chen, Qiming; Dayal, Umeshwar; Hsu, Meichun D. Georgakopoulos, A. Buchmann (eds.) (2001). 215–224.
• FreeSpan: frequent pattern-projected sequential pattern mining. Han, Jiawei; Pei, Jian; Mortazavi-Asl, Behzad; Chen, Qiming; Dayal, Umeshwar; Hsu, Meichun R. Ramakrishnan, S. J. Stolfo, R. J. Bayardo, I. Parsa (eds.) (2000). 355–359.
• Humanisme de l’Autre Homme Lévinas, Emmanuel (1972). LGF/Le Livre de Poche, [Montpellier].