Jun Yang
Bishop-MacDermott Family Professor
Department of Computer Science
Duke University
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Published Work

  1. Rickard Stureborg, Jenna Nichols, Bhuwan Dhingra, Jun Yang, Walter Orenstein, Robert A. Bednarczyk, and Lavanya Vasudevan. "Development and validation of VaxConcerns: a taxonomy of vaccine concerns and misinformation with crowdsource-viability." Vaccine, 2024. [link]
  2. Yihao Hu, Amir Gilad, Kristin Stephens-Martinez, Sudeepa Roy, and Jun Yang. "Qr-Hint: actionable hints towards correcting wrong SQL queries." In Proceedings of the 2024 ACM SIGMOD International Conference on Management of Data, Santiago, Chile, June 2024.
  3. Pankaj K. Agarwal, Xiao Hu, Stavros Sintos, and Jun Yang. "On reporting durable patterns in temporal proximity graphs." In Proceedings of the 2024 ACM Symposium on Principles of Database Systems, Santiago, Chile, June 2024.
  4. Pankaj Agarwal, Rahul Raychaudhury, Stavros Sintos, and Jun Yang. "Computing data distribution from query selectivities." In Proceedings of the 2024 International Conference on Database Theory, Paestum, Italy, March 2024.
  5. Hanze Meng, Zhengjie Miao, Amir Gilad, Sudeepa Roy, and Jun Yang. "Characterizing and verifying queries via CInsGen." In Proceedings of the 2023 ACM SIGMOD International Conference on Management of Data, Seattle, Washington, USA, June 2023. Demonstration track.
  6. Rickard Stureborg, Bhuwan Dhingra, and Jun Yang. "Interface design for crowdsourcing hierarchical multi-label text annotations." In Proceedings of the 2023 International Conference on Human Factors in Computing Systems, Hamburg, Germany, April 2023.
  7. Sudeepa Roy and Jun Yang, ed. Special Issue on Widening the Impact of Data Engineering through Innovations in Education, Interfaces, and Features, IEEE Data Engineering Bulletin, September 2022. 45(3). [link]
  8. Xiao Hu, Stavros Sintos, Junyang Gao, Pankaj Agarwal, and Jun Yang. "Computing complex temporal join queries efficiently." In Proceedings of the 2022 ACM SIGMOD International Conference on Management of Data, Philadelphia, Pennsylvania, USA, June 2022.
  9. Xiao Hu, Yuxi Liu, Haibo Xiu, Pankaj Agarwal, Debmalya Panigrahi, Sudeepa Roy, and Jun Yang. "Selectivity functions of range queries are learnable." In Proceedings of the 2022 ACM SIGMOD International Conference on Management of Data, Philadelphia, Pennsylvania, USA, June 2022.
  10. Amir Gilad, Zhengjie Miao, Sudeepa Roy, and Jun Yang. "Understanding queries by conditional instances." In Proceedings of the 2022 ACM SIGMOD International Conference on Management of Data, Philadelphia, Pennsylvania, USA, June 2022.
  11. Yihao Hu, Zhengjie Miao, Zhiming Leong, Haechan Lim, Zachary Zheng, Sudeepa Roy, Kristin Stephens-Martinez, and Jun Yang. "I-Rex: an interactive relational query debugger for SQL." In Proceedings of the 2022 ACM Technical Symposium on Computer Science Education, Providence, Rhode Island, USA, March 2022. Demonstration track.
  12. Guoliang Li, Guo Yu, Jun Yang, and Ju Fan, ed. Special Topic on New Techniques of Database Systems, Journal of Software (Ruanjian Xuebao), March 2022. 33(3).
  13. Chengkai Li and Jun Yang, ed. Special Issue on Data Engineering Challenges in Combating Misinformation, IEEE Data Engineering Bulletin, September 2021. 44(3). [link]
  14. Pankaj K. Agarwal, Xiao Hu, Stavros Sintos, and Jun Yang. "Dynamic enumeration of similarity joins." In Proceedings of the 2021 International Colloquium on Automata, Languages, and Programming, pages 11:1-11:19, Glasgow, Scotland, July 2021.
  15. Junyang Gao, Yifan Xu, Pankaj Agarwal, and Jun Yang. "Efficiently answering durability prediction queries." In Proceedings of the 2021 ACM SIGMOD International Conference on Management of Data, pages 591-604, Xi'an, China, June 2021.
  16. Junyang Gao, Stavros Sintos, Pankaj K. Agarwal, and Jun Yang. "Durable top-k instant-stamped temporal records with user-specified scoring functions." In Proceedings of the 2021 International Conference on Data Engineering, pages 720-731, Chania, Greece, April 2021.
  17. Chenghong Wang, David Pujol, Yanping Zhang, Johes Bater, Matthew Lentz, Ashwin Machanavajjhala, Kartik Nayak, Lavanya Vasudevan, and Jun Yang. "Poirot: private contact summary aggregation." In Proceedings of the 2020 Privacy Preserving Machine Learning (NeurIPS Workshop), Virtual, December 2020.
  18. Yanping Zhang, Chenghong Wang, David Pujol, Johes Bater, Matthew Lentz, Ashwin Machanavajjhala, Kartik Nayak, Lavanya Vasudevan, and Jun Yang. "Poirot: private contact summary aggregation." In Proceedings of the 2020 ACM Conference on Embedded Networked Sensor Systems, Yokohama, Japan, November 2020. Poster track. Part of the research poster track on COVID-19 pandemic response.
  19. Zhengjie Miao, Tiangang Chen, Alexander Bendeck, Kevin Day, Sudeepa Roy, and Jun Yang. "I-Rex: an interactive relational query explainer for SQL." Proceedings of the VLDB Endowment, 13(12):2997-3000, August 2020. Demonstration description.
  20. Brett Walenz, Stavros Sintos, Sudeepa Roy, and Jun Yang. "Learning to sample: counting with complex queries." Proceedings of the VLDB Endowment, 13(3):390-402, 2019.
  21. Stavros Sintos, Pankaj Agarwal, and Jun Yang. "Selecting data to clean for fact checking: minimizing uncertainty vs. maximizing surprise." Proceedings of the VLDB Endowment, 12(13):2408-2421, 2019.
  22. Junyang Gao, Xian Li, Yifan Ethan Xu, Bunyamin Sisman, Xin Luna Dong, and Jun Yang. "Efficient knowledge graph accuracy evaluation." Proceedings of the VLDB Endowment, 12(11):1679-1691, 2019. [report]
  23. Naeemul Hassan, Chengkai Li, Jun Yang, and Cong Yu, ed. Special Issue on Combating Digital Misinformation and Disinformation, ACM Journal of Data and Information Quality, July 2019. 11(3). [link]
  24. Zhengjie Miao, Sudeepa Roy, and Jun Yang. "RATest: explaining wrong relational queries using small examples." In Proceedings of the 2019 ACM SIGMOD International Conference on Management of Data, pages 1961-1964, Amsterdam, Netherlands, June 2019. Demonstration track. [paper]
  25. Zhengjie Miao, Sudeepa Roy, and Jun Yang. "Explaining wrong queries using small examples." In Proceedings of the 2019 ACM SIGMOD International Conference on Management of Data, pages 503-520, Amsterdam, Netherlands, June 2019. [paper]
  26. Guoliang Li, Jun Yang, João Gama, Juggapong Natwichai, and Yongxin Tong, ed. Proceedings of the 2019 International Conference on Database Systems for Advanced Applications, Chiang Mai, Thailand, April 2019. Lecture Notes in Computer Science 11447. Springer. ISBN: 978-3-030-18578-7.
  27. Matthias Boehm, Arun Kumar, and Jun Yang. Data management in machine learning systems. Morgan & Claypool Publishers, February 2019. [paper]
  28. Bill Adair, Chengkai Li, Jun Yang, and Cong Yu. "Automated pop-up fact-checking: challenges and progress." In Proceedings of the 2019 Computation+Journalism Symposium, Miami, Florida, USA, February 2019. Informal publication. [paper]
  29. Jun Yang, Pankaj K. Agarwal, Sudeepa Roy, Brett Walenz, You Wu, Cong Yu, and Chengkai Li. "Query perturbation analysis: an adventure of database researchers in fact-checking." IEEE Data Engineering Bulletin, 41(3):28-42, 2018. Invited contribution. [paper]
  30. Yuhao Wen, Xiaodan Zhu, Sudeepa Roy, and Jun Yang. "Interactive summarization and exploration of top aggregate query answers." Proceedings of the VLDB Endowment, 11(13):2196-2208, 2018. [paper]
  31. Junyang Gao, Pankaj Agarwal, and Jun Yang. "Durable top-k queries on temporal data." Proceedings of the VLDB Endowment, 11(13):2223-2235, 2018. [paper]
  32. Yuhao Wen, Xiaodan Zhu, Sudeepa Roy, and Jun Yang. "QAGView: interactively summarizing high-valued aggregate query answers." In Proceedings of the 2018 ACM SIGMOD International Conference on Management of Data, pages 1709-1712, Houston, Texas, USA, June 2018. Demonstration track. [paper]
  33. Bill Adair, Chengkai Li, Jun Yang, and Cong Yu. "Progress toward “the holy grail”: the continued quest to automate fact-checking." In Proceedings of the 2017 Computation+Journalism Symposium, Evanston, Illinois, USA, October 2017. Informal publication.
  34. Brett Walenz, Sudeepa Roy, and Jun Yang. "Optimizing iceberg queries with complex joins." In Proceedings of the 2017 ACM SIGMOD International Conference on Management of Data, pages 1243-1258, Chicago, Illinois, USA, May 2017. [paper]
  35. Arun Kumar, Matthias Boehm, and Jun Yang. "Data management in machine learning: challenges, techniques, and systems." In Proceedings of the 2017 ACM SIGMOD International Conference on Management of Data, pages 1717-1722, Chicago, Illinois, USA, May 2017. [paper]
  36. Semih Salihoglu, Wenchao Zhou, Rada Chirkova, Jun Yang, and Dan Suciu, ed. Proceedings of the 2017 ACM SIGMOD International Conference on Management of Data, Chicago, Illinois, USA, May 2017.
  37. Risi Thonangi and Jun Yang. "On log-structured merge for solid-state drives." In Proceedings of the 2017 International Conference on Data Engineering, pages 683-694, San Diego, California, USA, April 2017. [paper]
  38. Botong Huang and Jun Yang. "Cümülön-D: data analytics in a dynamic spot market." Proceedings of the VLDB Endowment, 10(8):865-876, April 2017. [paper]
  39. You Wu, Junyang Gao, Pankaj K. Agarwal, and Jun Yang. "Finding diverse, high-value representatives on a surface of answers." Proceedings of the VLDB Endowment, 10(7):793-804, March 2017. [paper]
  40. You Wu, Pankaj K. Agarwal, Chengkai Li, Jun Yang, and Cong Yu. "Computational fact checking through query perturbations." ACM Transactions on Database Systems, 42(1):4:1-4:41, March 2017. [paper]
  41. Albert Yu, Pankaj K. Agarwal, and Jun Yang. "Top-k preferences in high dimensions." IEEE Transactions on Knowledge and Data Engineering, 28(2):311-325, 2016. Invited as a special selection from ICDE 2014. [paper]
  42. Brett Walenz and Jun Yang. "Perturbation analysis of database queries." Proceedings of the VLDB Endowment, 9(14):1635-1646, September 2016. [paper and report]
  43. Brett Walenz, Junyang Gao, Emre Sonmez, Yubo Tian, Yuhao Wen, Charles Xu, Bill Adair, and Jun Yang. "Fact checking congressional voting claims." In Proceedings of the 2016 Computation+Journalism Symposium, Stanford, California, USA, September 2016. Informal publication. [paper]
  44. Naeemul Hassan, Bill Adair, James T. Hamilton, Chengkai Li, Mark Tremayne, Jun Yang, and Cong Yu. "The quest to automate fact-checking." In Proceedings of the 2015 Computation+Journalism Symposium, New York City, New York, USA, October 2015. Informal publication. [paper]
  45. Botong Huang, Nicholas W. D. Jarrett, Shivnath Babu, Sayan Mukherjee, and Jun Yang. "Cümülön: matrix-based data analytics in the cloud with spot instances." Proceedings of the VLDB Endowment, 9(3):156-167, September 2015. [paper and report]
  46. You Wu, Boulos Harb, Jun Yang, and Cong Yu. "Efficient evaluation of object-centric exploration queries for visualization." Proceedings of the VLDB Endowment, 8(12):1752-1763, August 2015. [paper]
  47. Jun Yang, ed. Special Issue on Visionary Ideas in Data Management, ACM SIGMOD Record, June 2015. 44(2). [link]
  48. You Wu, Pankaj K. Agarwal, Chengkai Li, Jun Yang, and Cong Yu. "Toward computational fact-checking." Proceedings of the VLDB Endowment, 7(7):589-600, 2014. [paper]
  49. Naeemul Hassan, Afroza Sultana, You Wu, Gensheng Zhang, Chengkai Li, Jun Yang, and Cong Yu. "Data in, fact out: automated monitoring of facts by FactWatcher." Proceedings of the VLDB Endowment, 7(13), 2014. Demonstration track. Winner of the Excellent Demonstration Award. [paper]
  50. Brett Walenz, You Wu, Seokhyun Song, Emre Sonmez, Eric Wu, Kevin Wu, Pankaj K. Agarwal, Jun Yang, Naeemul Hassan, Afroza Sultana, Gensheng Zhang, Chengkai Li, and Cong Yu. "Finding, monitoring, and checking claims computationally based on structured data." In Proceedings of the 2014 Computation+Journalism Symposium, New York City, New York, USA, October 2014. Informal publication, with contents drawn from SIGMOD 2014 and VLDB 2014 demos. [paper]
  51. Bill Adair, Jun Yang, and the uclaim/icheck Team. "Turning computers into fact-checkers." American Journalism Review, October 2014. Invited contribution. [link and paper]
  52. Botong Huang, Nicholas W. D. Jarrett, Shivnath Babu, Sayan Mukherjee, and Jun Yang. "Cumulon: cloud-based statistical analysis from users' perspective." IEEE Data Engineering Bulletin, 37(3):77-89, September 2014. Invited contribution. [paper]
  53. Rada Chirkova and Jun Yang, ed. Proceedings of the 2014 International Workshop on Bringing the Value of Big Data to Users, Hangzhou, China, September 2014. [link]
  54. You Wu, Brett Walenz, Peggy Li, Andrew Shim, Emre Sonmez, Pankaj K. Agarwal, Chengkai Li, Jun Yang, and Cong Yu. "iCheck: computationally combating “lies, d—ned lies, and statistics”." In Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, Snowbird, Utah, USA, June 2014. Demonstration track. [paper]
  55. Albert Yu, Pankaj K. Agarwal, and Jun Yang. "Top-k preferences in high dimensions." In Proceedings of the 2014 International Conference on Data Engineering, Chicago, Illinois, USA, March 2014. Results in this paper are subsumed by those in the TKDE 2016 paper by the same authors.
  56. Afroza Sultana, Naeemul Hassan, Chengkai Li, Jun Yang, and Cong Yu. "Incremental discovery of prominent situational facts." In Proceedings of the 2014 International Conference on Data Engineering, Chicago, Illinois, USA, March 2014. [paper and slides]
  57. Risi Thonangi and Jun Yang. "Permuting data on random-access block storage." Proceedings of the VLDB Endowment, 6(9):721-732, 2013. [errata, paper, and report]
  58. Botong Huang, Shivnath Babu, and Jun Yang. "Cumulon: optimizing statistical data analysis in the cloud." In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, New York City, New York, USA, June 2013. [paper and slides]
  59. Yi Zhang, Kristian Lum, and Jun Yang. "Failure-aware cascaded suppression in wireless sensor networks." IEEE Transactions on Knowledge and Data Engineering, 25(5):1042-1055, May 2013. [paper and supplemental]
  60. Pankaj K. Agarwal, Lars Arge, Sathish Govindarajan, Jun Yang, and Ke Yi. "Efficient external memory structures for range-aggregate queries." Computational Geometry: Theory and Applications, 46(3):358-370, April 2013. [paper]
  61. Albert Yu, Pankaj K. Agarwal, and Jun Yang. "Subscriber assignment for wide-area content-based publish/subscribe." IEEE Transactions on Knowledge and Data Engineering, 24(10):1833-1847, 2012. Invited as a special selection from ICDE 2011. [paper and supplemental]
  62. S. N. Lahiri, XuanLong Nguyen, Jun Yang, Zhengyuan Zhu, and P. Banerjee. "Wireless sensor networks: statistical issues and challenges." Journal of the Indian Statistical Association, 50(1–2):151-191, 2012.
  63. Rada Chirkova and Jun Yang. "Materialized views." Foundations and Trends in Databases, 4(4):295-405, 2012. [paper]
  64. Risi Thonangi, Shivnath Babu, and Jun Yang. "A practical concurrent index for solid-state drives." In Proceedings of the 2012 International Conference on Information and Knowledge Management, pages 1332-1341, Maui, Hawaii, USA, October 2012. Databases track. [paper and report]
  65. You Wu, Pankaj K. Agarwal, Chengkai Li, Jun Yang, and Cong Yu. "On “one of the few” objects." In Proceedings of the 2012 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1487-1495, Beijing, China, August 2012. [paper and report]
  66. Yi Zhang and Jun Yang. "Optimizing I/O for big array analytics." Proceedings of the VLDB Endowment, 5(8):764-775, June 2012. [paper]
  67. Albert Yu, Pankaj K. Agarwal, and Jun Yang. "Processing a large number of continuous preference top-k queries." In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pages 397-408, Scottsdale, Arizona, USA, May 2012. [paper]
  68. Albert Yu, Pankaj K. Agarwal, and Jun Yang. "Processing and notifying range top-k subscriptions." In Proceedings of the 2012 International Conference on Data Engineering, pages 810-821, Washington DC, USA, April 2012. [paper and report]
  69. Yi Zhang, Kamesh Munagala, and Jun Yang. "Storing matrices on disk: theory and practice revisited." Proceedings of the VLDB Endowment, 4(11):1075-1086, August 2011. [paper and report]
  70. James S. Clark, Pankaj K. Agarwal, David M. Bell, Paul G. Flikkema, Alan Gelfand, Xuanlong Nguyen, Eric Ward, and Jun Yang. "Inferential ecosystem models, from network data to prediction." Ecological Applications, 21(5):1523-1536, July 2011.
  71. Albert Yu, Pankaj K. Agarwal, and Jun Yang. "Subscriber assignment for wide-area content-based publish/subscribe." In Proceedings of the 2011 International Conference on Data Engineering, pages 267-278, Hannover, Germany, April 2011. Results in this paper are subsumed by those in the TKDE 2012 paper by the same authors. [paper and report]
  72. Sarah Cohen, Chengkai Li, Jun Yang, and Cong Yu. "Computational journalism: a call to arms to database researchers." In Proceedings of the 2011 Conference on Innovative Data Systems Research, Asilomar, California, USA, January 2011. Outrageous ideas and vision track. Third-place winner of the Best Outrageous Ideas and Vision Track Paper Competition sponsored by the Computing Community Consortium. [paper and slides]
  73. Lei Chen, Changjie Tang, Jun Yang, and Yunjun Gao, ed. Proceedings of the 2010 International Conference on Web-Age Information Management, Jiuzhaigou, Sichuan, China, July 2010. Lecture Notes in Computer Science 6184. Springer. ISBN: 978-3-642-14245-1.
  74. Yi Zhang, Weiping Zhang, and Jun Yang. "I/O-efficient statistical computing with RIOT." In Proceedings of the 2010 International Conference on Data Engineering, pages 1157-1160, Long Beach, California, USA, March 2010. Demonstration track. [paper and poster]
  75. Jun Yang, Kamesh Munagala, and Adam Silberstein. "Data aggregation in sensor networks." In Encyclopedia of Database Systems. Ling Liu and M. Tamer Özsu, ed. Springer. 2009. Invited contribution.
  76. Albert Yu, Pankaj K. Agarwal, and Jun Yang. "Generating wide-area content-based publish/subscribe workloads." In Proceedings of the 2009 Workshop on Networking Meets Databases, Big Sky, Montana, USA, October 2009. [paper]
  77. Pankaj K. Agarwal, Junyi Xie, Jun Yang, and Hai Yu. "Input-sensitive scalable continuous join query processing." ACM Transactions on Database Systems, 34(3):1-41, August 2009. [paper]
  78. Fei Chen, Byron J. Gao, AnHai Doan, Jun Yang, and Raghu Ramakrishnan. "Optimizing complex extraction programs over evolving text data." In Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, pages 321-334, Providence, Rhode Island, USA, June 2009. [paper]
  79. Risi Thonangi, Hao He, AnHai Doan, Haixun Wang, and Jun Yang. "Weighted proximity best-joins for information retrieval." In Proceedings of the 2009 International Conference on Data Engineering, pages 234-245, Shanghai, China, March 2009. [paper]
  80. Yi Zhang, Herodotos Herodotou, and Jun Yang. "RIOT: I/O-efficient numerical computing without SQL." In Proceedings of the 2009 Conference on Innovative Data Systems Research, Asilomar, California, USA, January 2009. [paper and slides]
  81. Badrish Chandramouli and Jun Yang. "End-to-end support for joins in large-scale publish/subscribe systems." In Proceedings of the 2008 International Conference on Very Large Data Bases, pages 434-450, Auckland, New Zealand, August 2008. Infrastructure track. [paper]
  82. Badrish Chandramouli, Jun Yang, Pankaj K. Agarwal, Albert Yu, and Ying Zheng. "ProSem: scalable wide-area publish/subscribe." In Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pages 1315-1318, Vancouver, Canada, June 2008. Demonstration track. Acceptance rate: 31.9 percent. [paper]
  83. Junyi Xie, Jun Yang, Yuguo Chen, Haixun Wang, and Philip S. Yu. "A sampling-based approach to information recovery." In Proceedings of the 2008 International Conference on Data Engineering, pages 476-485, Cancun, Mexico, April 2008. Short presentation track. Acceptance rate: 19.2 percent of 715. Full paper. [paper]
  84. Fei Chen, AnHai Doan, Jun Yang, and Raghu Ramakrishnan. "Efficient information extraction over evolving text data." In Proceedings of the 2008 International Conference on Data Engineering, pages 943-952, Cancun, Mexico, April 2008. Acceptance rate: 12.1 percent of 715. [paper]
  85. Magdalena Balazinska, Amol Deshpande, Alexandros Labrinidis, Qiong Luo, Samuel Madden, and Jun Yang. "Report on the fourth international workshop on data management for sensor networks (DMSN 2007)." ACM SIGMOD Record, 36(4):53-55, 2007.
  86. Adam Silberstein, Gavino Puggioni, Alan E. Gelfand, Kamesh Munagala, and Jun Yang. "Suppression and failures in sensor data: a Bayesian approach." In Proceedings of the 2007 International Conference on Very Large Data Bases, pages 842-853, Vienna, Austria, September 2007. Infrastructure track. Acceptance rate: 45 out of 275. [paper]
  87. Badrish Chandramouli, Jeff M. Phillips, and Jun Yang. "Value-based notification conditions in large-scale publish/subscribe systems." In Proceedings of the 2007 International Conference on Very Large Data Bases, pages 878-889, Vienna, Austria, September 2007. Infrastructure track. Acceptance rate: 45 out of 275. [paper]
  88. Magdalena Balazinska, Amol Deshpande, Qiong Luo, and Jun Yang, ed. Proceedings of the 2007 International Workshop on Data Management for Sensor Networks, Vienna, Austria, September 2007.
  89. Hao He, Haixun Wang, Jun Yang, and Philip S. Yu. "BLINKS: ranked keyword searches on graphs." In Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pages 305-316, Beijing, China, June 2007. Acceptance rate: 70 out of 480. [paper and report]
  90. Badrish Chandramouli, Christopher N. Bond, Shivnath Babu, and Jun Yang. "Query suspend and resume." In Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pages 557-568, Beijing, China, June 2007. Acceptance rate: 70 out of 480. [paper and report]
  91. Adam Silberstein and Jun Yang. "Many-to-many aggregation for sensor networks." In Proceedings of the 2007 International Conference on Data Engineering, pages 986-995, Istanbul, Turkey, April 2007. Acceptance rate: 122 out of 659. [paper and report]
  92. Badrish Chandramouli, Christopher Bond, Shivnath Babu, and Jun Yang. "On suspending and resuming dataflows." In Proceedings of the 2007 International Conference on Data Engineering, pages 1289-1291, Istanbul, Turkey, April 2007. Poster track. Acceptance rate: 60(+122) out of 659. Results in this paper are subsumed by those in the SIGMOD 2007 paper by the same authors.
  93. Adam Silberstein, Gregory Filpus, Kamesh Munagala, and Jun Yang. "Data-driven processing in sensor networks." In Proceedings of the 2007 Conference on Innovative Data Systems Research, pages 10-21, Asilomar, California, USA, January 2007. Acceptance rate: 34 out of 98. [paper]
  94. Junyi Xie and Jun Yang. "A survey of join processing in data streams." In Data Streams: Models and Algorithms. Charu C. Aggarwal, ed. Springer. November 2006. Invited contribution. [paper]
  95. Pankaj K. Agarwal, Junyi Xie, Jun Yang, and Hai Yu. "Scalable continuous query processing by tracking hotspots." In Proceedings of the 2006 International Conference on Very Large Data Bases, pages 31-42, Seoul, Korea, September 2006. Core database track. Acceptance rate: 46 out of 334. Results in this paper are subsumed by those in the 2009 TODS paper by the same authors. [paper and report]
  96. Adam Silberstein, Kamesh Munagala, and Jun Yang. "Energy-efficient monitoring of extreme values in sensor networks." In Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, pages 169-180, Chicago, Illinois, USA, June 2006. Acceptance rate: 58 out of 446. [paper]
  97. Adam Silberstein, Rebecca Braynard, and Jun Yang. "Constraint chaining: on energy-efficient continuous monitoring in sensor networks." In Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, pages 157-168, Chicago, Illinois, USA, June 2006. Acceptance rate: 58 out of 446. [paper]
  98. Badrish Chandramouli, Junyi Xie, and Jun Yang. "On the database/network interface in large-scale publish/subscribe systems." In Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, pages 587-598, Chicago, Illinois, USA, June 2006. Acceptance rate: 58 out of 446. [paper and report]
  99. Paul G. Flikkema, Pankaj K. Agarwal, James S. Clark, Carla Schlatter Ellis, Alan Gelfand, Kamesh Munagala, and Jun Yang. "Model-driven dynamic control of embedded wireless sensor networks." In Proceedings of the 2006 International Conference on Computational Science, pages 409-416, Reading, United Kingdom, May 2006.
  100. Haixun Wang, Hao He, Jun Yang, Philip S. Yu, and Jeffrey Xu Yu. "Dual labeling: answering graph reachability queries in constant time." In Proceedings of the 2006 International Conference on Data Engineering, Atlanta, Georgia, USA, April 2006. Acceptance rate: 89 out of 456. [paper]
  101. Adam Silberstein, Rebecca Braynard, and Jun Yang. "Energy-efficient continuous isoline queries in sensor networks." In Proceedings of the 2006 International Conference on Data Engineering, Atlanta, Georgia, USA, April 2006. Poster track. Results in this paper are subsumed by those in the SIGMOD 2006 paper by the same authors. [paper]
  102. Adam Silberstein, Rebecca Braynard, Carla Ellis, Kamesh Munagala, and Jun Yang. "A sampling-based approach to optimizing top-k queries in sensor networks." In Proceedings of the 2006 International Conference on Data Engineering, Atlanta, Georgia, USA, April 2006. Acceptance rate: 89 out of 456. [paper]
  103. Badrish Chandramouli, Jun Yang, and Amin Vahdat. "Distributed network querying with bounded approximate caching." In Proceedings of the 2006 International Conference on Database Systems for Advanced Applications, pages 374-388, Singapore, April 2006. Acceptance rate: 24.5 percent. [paper and report]
  104. Pankaj K. Agarwal, Junyi Xie, Jun Yang, and Hai Yu. "Monitoring continuous band-join queries over dynamic data." In Proceedings of the 2005 International Symposium on Algorithms and Computation, pages 349-359, Sanya, Hainan, China, December 2005. [paper]
  105. Hao He, Haixun Wang, Jun Yang, and Philip S. Yu. "Compact reachability labeling for graph-structured data." In Proceedings of the 2005 International Conference on Information and Knowledge Management, pages 594-601, Bremen, Germany, November 2005. Acceptance rate: 76 out of 425. [paper and report]
  106. Kamesh Munagala, Jun Yang, and Hai Yu. "Online view maintenance under a response-time constraint." In Proceedings of the 2005 European Symposium on Algorithms, pages 677-688, Palma de Mallorca, Spain, October 2005. [paper]
  107. Wenfei Fan, Zhaohui Wu, and Jun Yang, ed. Proceedings of the 2005 International Conference on Web-Age Information Management, Hangzhou, China, October 2005. Lecture Notes in Computer Science 3739. Springer. ISBN: 3-540-29227-6.
  108. Junyi Xie, Jun Yang, and Yuguo Chen. "On joining and caching stochastic streams." In Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pages 359-370, Baltimore, Maryland, USA, June 2005. Acceptance rate: 65 out of 431. [paper and report]
  109. Adam Silberstein, Hao He, Ke Yi, and Jun Yang. "BOXes: efficient maintenance of order-based labeling for dynamic XML data." In Proceedings of the 2005 International Conference on Data Engineering, pages 285-296, Tokyo, Japan, April 2005. Acceptance rate: 67 out of 521. [paper and report]
  110. Hao He, Junyi Xie, Jun Yang, and Hai Yu. "Asymmetric batch incremental view maintenance." In Proceedings of the 2005 International Conference on Data Engineering, pages 106-117, Tokyo, Japan, April 2005. Acceptance rate: 67 out of 521. [paper]
  111. Junfei Geng and Jun Yang. "AutoBib: automatic extraction of bibliographic information on the Web." In Proceedings of the 2004 International Database Engineering and Applications Symposium, pages 193-204, Coimbra, Portugal, July 2004. [paper]
  112. Ke Yi, Hao He, Ioana Stanoi, and Jun Yang. "Incremental maintenance of XML structural indexes." In Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data, pages 491-502, Paris, France, June 2004. Acceptance rate: 69 out of 431. [paper]
  113. Adam Silberstein and Jun Yang. "NeXSort: sorting XML in external memory." In Proceedings of the 2004 International Conference on Data Engineering, pages 695-706, Boston, Massachusetts, USA, April 2004. Acceptance rate: 63 out of 441. [paper and report]
  114. Hao He and Jun Yang. "Multiresolution indexing of XML for frequent queries." In Proceedings of the 2004 International Conference on Data Engineering, pages 683-694, Boston, Massachusetts, USA, April 2004. Acceptance rate: 63 out of 441. [paper and report]
  115. Jun Yang and Jennifer Widom. "Incremental computation and maintenance of temporal aggregates." The VLDB Journal, 12(3):262-283, 2003. [paper]
  116. Zhiyuan Chen, Li Chen, Jian Pei, Yufei Tao, Haixun Wang, Wei Wang, Jiong Yang, Jun Yang, and Donghui Zhang. "Recent progress on selected topics in database research: a report by nine young chinese researchers working in the united states." Journal of Computer Science and Technology, 18(5):538-552, September 2003.
  117. Pankaj K. Agarwal, Lars Arge, Jun Yang, and Ke Yi. "I/O-efficient structures for orthogonal range-max and stabbing-max queries." In Proceedings of the 2003 European Symposium on Algorithms, pages 7-18, Budapest, Hungary, September 2003.
  118. Xiao Huang, Qiang Xue, and Jun Yang. "TupleRank and implicit relationship discovery in relational databases." In Proceedings of the 2003 International Conference on Web-Age Information Management, pages 445-457, Chengdu, China, August 2003. Acceptance rate: 30 out of 258. [paper and report]
  119. Ke Yi, Hai Yu, Jun Yang, Gangqiang Xia, and Yuguo Chen. "Efficient maintenance of materialized top-k views." In Proceedings of the 2003 International Conference on Data Engineering, pages 189-200, Bangalore, India, March 2003. Acceptance rate: 51 out of 378. [paper and report]
  120. Jun Yang. "Temporal data warehousing." Ph.D. Dissertation, Stanford University, August 2001.
  121. Jun Yang and Jennifer Widom. "Incremental computation and maintenance of temporal aggregates." In Proceedings of the 2001 International Conference on Data Engineering, pages 51-60, Heidelberg, Germany, April 2001. Acceptance rate: 14 percent. Results in this paper are subsumed by those in the 2003 VLDB Journal paper by the same authors
  122. Wilburt Juan Labio, Jun Yang, Yingwei Cui, Hector Garcia-Molina, and Jennifer Widom. "Performance issues in incremental warehouse maintenance." In Proceedings of the 2000 International Conference on Very Large Data Bases, pages 461-472, Cairo, Egypt, September 2000. Acceptance rate: 53 out of 351.
  123. Jun Yang, Huacheng C. Ying, and Jennifer Widom. "TIP: a temporal extension to informix." In Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, page 596, Dallas, Texas, USA, May 2000. Demonstration track.
  124. Jun Yang, Huacheng C. Ying, and Jennifer Widom. "TIP: a temporal extension to informix." In Proceedings of the 2000 International Conference on Extending Database Technology, Konstanz, Germany, March 2000. Demonstration track. An improved version was shown in SIGMOD 2000.
  125. Jun Yang and Jennifer Widom. "Temporal view self-maintenance." In Proceedings of the 2000 International Conference on Extending Database Technology, pages 395-412, Konstanz, Germany, March 2000. Acceptance rate: 16.7 percent.
  126. Hector Garcia-Molina, Wilburt Juan Labio, and Jun Yang. "Expiring data in a warehouse." In Proceedings of the 1998 International Conference on Very Large Data Bases, pages 500-511, New York City, New York, USA, August 1998. Acceptance rate: 16 percent.
  127. Jun Yang and Jennifer Widom. "Maintaining temporal views over non-temporal information sources for data warehousing." In Proceedings of the 1998 International Conference on Extending Database Technology, pages 389-403, Valencia, Spain, March 1998. Acceptance rate: 32 out of 191.
  128. Laura M. Haas, Donald Kossmann, Edward L. Wimmers, and Jun Yang. "Optimizing queries across diverse data sources." In Proceedings of the 1997 International Conference on Very Large Data Bases, pages 276-285, Athens, Greece, August 1997. Acceptance rate: 16 percent.
  129. Laura M. Haas, Donald Kossmann, Edward L. Wimmers, and Jun Yang. "An optimizer for heterogeneous systems with non-standard data and search capabilities." IEEE Data Engineering Bulletin, 19(4):37-44, December 1996.
  130. Steve G. Steinberg, Jun Yang, and Katherine A. Yelick. "Performance modeling and composition: a case study in cell simulation." In Proceedings of the 1996 International Parallel Processing Symposium, pages 68-74, Honolulu, Hawaii, USA, April 1996. Acceptance rate: 35 percent.

Technical Reports

  • Kevin A. Walsh, Amin Vahdat, and Jun Yang. "Enabling wide-area replication of database services with continuous consistency." Technical Report, Duke University, February 2002. [report]
  • Jun Yang, Jennifer Widom, and Paul Brown. "Implementing parameterized range types in an extensible DBMS." Technical Report, Stanford University, November 2000.

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Last updated Mon Mar 25 08:08:27 EDT 2024