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PUBLICATIONS

Journal Papers
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  1. Jiaxing Xu, Qingtian Bian, Xinhang Li, Aihu Zhang, Yiping Ke, Miao Qiao, Wei Zhang, Wei Khang Jeremy Sim, and Balazs Gulyas. Contrastive Graph Pooling for Explainable Classification of Brain Networks. To appear in IEEE Transactions on Medical Imaging (TMI), 2024.

  2. Pengfei Wei, Yiping Ke, Yew-Soon Ong, and Zejun Ma. Adaptive Transfer Kernel Learning for Transfer Gaussian Process Regression. In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 45(6): 7142-7156, 2023.

  3. Pengfei Wei, Yiping Ke, Xinghua Qu, and Tze-Yun Leong. Subdomain Adaptation with Manifolds Discrepancy Alignment. In IEEE Transactions on Cybernetics, 52(11): 11698-11708, 2022.

  4. Pengfei Wei, Ramon Sagarna, Yiping Ke, and Yew-Soon Ong. Easy-but-Effective Domain Sub-Similarity Learning for Transfer Regression. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(9): 4161-4171, 2022.

  5. Pengfei Wei, Ramon Sagarna, Yiping Ke, and Yew-Soon Ong. Practical Multi-Source Transfer Regression with Source-Target Similarity Captures. In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 32(8): 3498-3509, 2021.

  6. Zhiqiang Xu, Yiping Ke, Xin Cao, Chunlai Zhou, Pengfei Wei, and Xin Gao. A Unified Linear Convergence Analysis of k-SVD. Memetic Computing, 12: 343-353, 2020.

  7. Pengfei Wei, Yiping Ke, and Chi Keong Goh. Feature Analysis of Marginalized Stacked Denoising Autoencoder for Unsupervised Domain Adaptation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 30(5): 1321-1334, 2019.

  8. Pengfei Wei, Yiping Ke, and Chi Keong Goh. A General Domain Specific Feature Transfer Framework for Hybrid Domain Adaptation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(8): 1440-1451, 2019.

  9. Shaista Hussain, Xavier Le Guezennec, Yi Wang, Dong Huang, Joanne Chia, Yiping Ke, Kee Khoon Lee, and Frederic Bard. Digging Deep into Golgi Phenotypic Diversity with Unsupervised Machine Learning. Molecular Biology of the Cell (MBoC), 28(25): 3686-3698, 2017. 

  10. Huanhuan Wu, James Cheng, Yiping Ke, Silu Huang, Yuzhen Huang, Hejun Wu. Efficient Algorithms for Temporal Path Computation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(11): 2927-2942, 2016.

  11. Zhiqiang Xu, Yiping Ke, Yi Wang, Hong Cheng, and James Cheng. GBAGC: A General Bayesian Framework for Attributed Graph Clustering. ACM Transactions on Knowledge Discovery from Data (TKDD), 9(1), 2014.

  12. Yuanyuan Zhu, Lu Qin, Jeffrey Xu Yu, Yiping Ke, and Xuemin Lin. High Efficiency and Quality: Large Graphs Matching. International Journal on Very Large Data Bases (VLDBJ), 22(3): 345-368, 2013.

  13. James Cheng, Yiping Ke, Ada Fu, Jeffrey Xu Yu, and Linhong Zhu. Finding Maximal Cliques in Massive Networks. ACM Transactions on Database Systems (TODS), 36(4): 21:1-21:34, 2011. Special issue on the best papers of SIGMOD 2010

  14. James Cheng, Yiping Ke, Ada Fu, and Jeffrey Xu Yu. Fast Graph Query Processing with a Low-Cost Index.  International Journal on Very Large Data Bases (VLDBJ), 20(4): 521-539, 2011.

  15. Di Wu, Yiping Ke, Jeffrey Xu Yu, Philip S. Yu, and Lei Chen. Leadership Discovery When Data Correlatively Evolve. World Wide Web Journal, 14(1): 1-25, 2011.

  16. James Cheng, Yiping Ke, and Wilfred Ng. Efficient Query Processing on Graph Databases. ACM Transactions on Database Systems (TODS), 34(1): 1-48, 2009.

  17. Yiping Ke, James Cheng, and Wilfred Ng. Correlated Pattern Mining in Quantitative Databases. ACM Transactions on Database Systems (TODS), 33(3): 1-45, 2008.

  18. Yiping Ke, James Cheng, and Wilfred Ng. Efficient Correlation Search from Graph Databases. IEEE Transactions on Knowledge and Data Engineering (TKDE), 20(12): 1601-1615, 2008.

  19. James Cheng, Yiping Ke, and Wilfred Ng. Effective Elimination of Redundant Association Rules. Data Mining and Knowledge Discovery (DMKD/DAMI), 16(2): 221-249, 2008.

  20. Yiping Ke, James Cheng, and Wilfred Ng. An Information-Theoretic Approach to Quantitative Association Rule Mining. Knowledge and Information Systems Journal (KAIS), 16(2): 213-244, 2008.

  21. James Cheng, Yiping Ke, and Wilfred Ng. Maintaining Frequent Closed Itemsets over a Sliding Window.  Journal of Intelligent Information Systems (JIIS), 31(3): 191-215, 2008.

  22. James Cheng, Yiping Ke, and Wilfred Ng. A Survey on Algorithms for Mining Frequent Patterns over Data Streams. Knowledge and Information Systems Journal (KAIS), 16(1): 1-27, 2008.

  23. Yiping Ke, Lin Deng, Wilfred Ng, and Dik Lun Lee. Web Dynamics and their Ramifications for the Development of Web Search Engines. Computer Networks Journal - Special Issue on "Web Dynamics", 50(10): 1430-1447, 2006.

Conference Papers
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  1. Tieying Li, Xiaochun Yang, Yiping Ke, Bin Wang, Yinan Liu, and Jiaxing Xu. Alleviating the Inconsistency of Multimodal Data in Cross-Modal Retrieval. To appear in Proceedings of the IEEE International Conference on Data Engineering (ICDE), 2024.
  2. Jiaxing Xu*, Aihu Zhang*, Qingtian Bian, Vijay Prakash Dwivedi, and Yiping Ke. Union Subgraph Neural Networks. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages 16173-16183, 2024.
  3. Mengcheng Lan, Xinjiang Wang, Yiping Ke, Jiaxing Xu, Litong Feng, and Wayne Zhang. SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation. In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
  4. Jiaxing Xu*, Yunhan Yang*, David Tse Jung Huang*, Sophi Shilpa Gururajapathy*, Yiping Ke, Miao Qiao, Alan Wang, Haribalan Kumar, Josh McGeown, and Eryn Kwon. Data-Driven Network Neuroscience: On Data Collection and Benchmark. In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2023.
  5. Qingtian Bian, Jiaxing Xu, Hui Fang, and Yiping Ke. CPMR: Context-Aware Incremental Sequential Recommendation with Pseudo-Multi-Task Learning. In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), pages 120-130, 2023.​​
  6. Tianbo Li, Tianze Luo, Yiping Ke, and Sinno Jialin Pan. Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions. In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 986-994, 2021.
  7. Pengfei Wei, Yiping Ke, Zhiqiang Xu, and Tze Yun Leong. Succinct Adaptive Manifold Transfer. In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), pages 1615-1624, 2020.
  8. Pengfei Wei, Xinghua Qu, Yiping Ke, Tze Yun Leong, and Yew Soon Ong. Adaptive Knowledge Transfer based on Transfer Neural Kernel Network. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 1485-1493, 2020.
  9. Tianbo Li and Yiping Ke. Tweedie-Hawkes Processes: Interpreting the Phenomena of Outbreaks. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages 4699-4706, 2020.
  10. Tianbo Li and Yiping Ke. Thinning for Accelerating the Learning of Point Processes. In Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS), pages 4093-4103, 2019.
  11. Pengfei Wei and Yiping Ke. Knowledge Transfer based on Multiple Manifolds Assumption. In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), pages 279-287, 2019.
  12. Tianbo Li, Pengfei Wei, and Yiping Ke. Transfer Hawkes Processes with Content Information. In Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 1116-1121, 2018.
  13. Pengfei Wei, Ramon Sagarna, Yiping Ke, and Yew Soon Ong. Uncluttered Domain Sub-Similarity Modeling for Transfer Regression. In Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 1314-1319, 2018.
  14. Vinod Rajendran, Yiping Ke, Edwin Leonardi, and Kevin Menzies. Vortex Detection on Unsteady CFD Simulations using Recurrent Neural Networks. In AIAA AVIATION Forum, 2018.
  15. Pengfei Wei, Yiping Ke, and Chi Keong Goh. Domain Specific Feature Transfer for Hybrid Domain Adaptation. In Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 1027-1032, 2017.
  16. Zhiqiang Xu, Yiping Ke, and Xin Gao. A Fast Stochastic Riemannian Eigensolver. In Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI), 2017.
  17. ​Pengfei Wei, Ramon Sagarna, Yiping Ke, Yew Soon Ong, and Chi Keong Goh. Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression. In Proceedings of the 34th International Conference on Machine Learning (ICML), pages 3722-3731, 2017.
  18. Zhiqiang Xu and Yiping Ke. Effective and Efficient Spectral Clustering on Text and Link Data. In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), pages 357-366, 2016.
  19. Pengfei Wei, Yiping Ke, and Chi Keong Goh. Deep Nonlinear Feature Coding for Unsupervised Domain Adaptation. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), pages 2189-2195, 2016.
  20. Huanhuan Wu, Yuzhen Huang, James Cheng, Jinfeng Li, and Yiping Ke. Reachability and Time-Based Path Queries in Temporal Graphs. In Proceedings of the IEEE International Conference on Data Engineering (ICDE), pages 145-156, 2016.
  21. Huanhuan Wu, James Cheng, Yi Lu, Yiping Ke, Yuzhen Huang, Da Yan, and Hejun Wu. Core Decomposition in Large Temporal Graphs. In Proceedings of the IEEE International Conference on Big Data, pages 649-658, 2015.
  22. Zhiqiang Xu, Yiping Ke, Yi Wang. A Fast Inference Algorithm for Stochastic Blockmodel. In Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 620-629, 2014.
  23. Huanhuan Wu, James Cheng, Silu Huang, Yiping Ke, Yi Lu, and Yanyan Xu. Path Problems in Temporal Graphs. In Proceedings of the 40th International Conference on Very Large Data Bases (VLDB), 7(9): 721-732, 2014.
  24. Zhiqiang Xu, Yiping Ke, Yi Wang, Hong Cheng, and James Cheng. A Model-based Approach to Attributed Graph Clustering. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 505-516, 2012.
  25. James Cheng, Yiping Ke, Shumo Chu, and Carter Cheng. Efficient Processing of Distance Queries in Large Graphs: A Vertex Cover Approach. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 457-468, 2012.
  26. James Cheng, Linhong Zhu, Yiping Ke, and Shumo Chu. Fast Algorithms for Maximal Clique Enumeration with Limited Memory. In Proceedings of the 18th ACM SIGKDD International Conferenceon Knowledge Discovery and Data Mining (KDD), pages 1240-1248, 2012.
  27. Yuanyuan Zhu, Lu Qin, Jeffrey Xu Yu, Yiping Ke, and Xuemin Lin. High Efficiency and Quality: Large Graphs Matching. In Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM), pages 1755-1764, 2011.
  28. James Cheng, Yiping Ke, Shumo Chu, M. Tamer Ozsu. Efficient Core Decomposition in Massive Networks. In Proceedings of the 27th IEEE International Conference on Data Engineering (ICDE), pages 51-62, 2011.
  29. James Cheng, Yiping Ke, Ada Fu, Jeffrey Xu Yu, and Linhong Zhu. Finding Maximal Cliques in Massive Networks by H*-Graph. In Proceedings of the 29th ACM SIGMOD International Conferenceon Management of Data (SIGMOD), pages 447-458, 2010.
  30. Di Wu, Yiping Ke, Jeffrey Xu Yu, Philip S. Yu, and Lei Chen. Detecting Leaders from Correlated Time Series. In Proceedings of the 15th International Conference on Database Systems for Advanced Applications (DASFAA), pages 352-367, 2010. Best Paper Award
  31. Qi Pan, Hong Cheng, Di Wu, Jeffrey Xu Yu, and Yiping Ke. Stock Risk Mining by News. In Proceedings of the 21st Australasian Database Conference (ADC), pages 179-188, 2010. Best PaperAward
  32. Yiping Ke, James Cheng, and Jeffrey Xu Yu. Efficient Discovery of Frequent Correlated Subgraph Pairs. In Proceedings of the 9th IEEE International Conference on Data Mining (ICDM), pages 239-248, 2009.
  33. James Cheng, Yiping Ke, and Wilfred Ng. Efficient Processing of Group-Oriented Connection Queries in a Large Graph. In Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM), pages 1481-1484, 2009.
  34. Yiping Ke, James Cheng, and Jeffrey Xu Yu. Top-k Correlative Graph Mining. In Proceedings of the 9th SIAM International Conference on Data Mining (SDM), pages 1038-1049, 2009.
  35. James Cheng, Yiping Ke, Wilfred Ng, and Jeffrey Xu Yu. Context-Aware Object Connection Discovery in Large Graphs. In Proceedings of the 25th IEEE International Conference on Data Engineering (ICDE), pages 856-867, 2009.
  36. Zheng Liu, Jeffrey Xu Yu, Yiping Ke, Xuemin Lin, and Lei Chen. Spotting Significant Changing Subgraphs in Evolving Graphs. In Proceedings of the 8th IEEE International Conference on DataMining (ICDM), pages 917-922, 2008.
  37. Yiping Ke, James Cheng, and Wilfred Ng. Correlation Search in Graph Databases. In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 390-399, 2007. (Nominated for Best Paper Award)
  38. James Cheng, Yiping Ke, Wilfred Ng and An Lu. FG-Index: Towards Verification-Free Query Processing on Graph Databases. In Proceedings of the 26th ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 857-872, 2007.
  39. An Lu, Yiping Ke, James Cheng, and Wilfred Ng. Mining Vague Association Rules. In Proceedings of the 12th International Conference on Database Systems for Advanced Applications (DASFAA), pages891-897, 2007.
  40. Yiping Ke, James Cheng, and Wilfred Ng. Mining Quantitative Correlated Patterns Using an Information-Theoretic Approach. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 227-236, 2006.
  41. James Cheng, Yiping Ke, and Wilfred Ng. 𝛿-Tolerance Closed Frequent Itemsets. In Proceedings of the 6th IEEE International Conference on Data Mining (ICDM), pages 139-148, 2006.
  42. James Cheng, Yiping Ke, and Wilfred Ng. Maintaining Frequent Itemsets over High-Speed Data Streams. In Proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pages 462-467, 2006.
  43. Yiping Ke, James Cheng, and Wilfred Ng. MIC Framework: An Information-Theoretic Approach to Quantitative Association Rule Mining. In Proceedings of the 22nd International Conference on Data Engineering (ICDE), page 112, 2006.
  44. Qingzhao Tan, Yiping Ke, and Wilfred Ng. WUML: A Web Usage Manipulation Language For Querying Web Log Data. In Proceedings of the 23rd International Conference on Conceptual Modeling (ER), pages 567-581, 2004.
Tutorials
 
  1. Yiping Ke, James Cheng, and Jeffrey Xu Yu. Querying Large Graph Databases. In the 15th International Conference on Database Systems for Advanced Applications (DASFAA), 2010.
Patents
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Granted:
  1. Yiping Ke, Jian Cheng Wong, Chi-Keong Goh, and Kee Khoon Lee. Vortex Identification Method. EP Patent 3113052, granted on 28 July 2023.
  2. Yiping Ke, Jian Cheng Wong, Chi-Keong Goh, and Kee Khoon Lee. Fluid Flow Feature Identification Methods and Tools. EP Patent EP3113053B1, granted on 10 August 2022.
  3. Yiping Ke, Jian Cheng Wong, Chi-Keong Goh, and Kee Khoon Lee. Fluid Flow Feature Identification Methods and Tools. US Patent 10591325B2, granted on 17 March 2020.
  4. Yiping Ke, Jian Cheng Wong, Chi-Keong Goh, and Kee Khoon Lee. Vortex Identification Methods and Tools. US Patent 10495543B2, granted on 3 December 2019.
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Filed:
  1. Yiping Ke, Erwin Leonardi, Jigang Liu, Mo Sha, and Kevin R. Menzies. Cross-Section Extraction for Vortex Detection. US Patent 20190303515A1, filed on 13 March 2019.
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