Duke Database Group Publications

2017


  1. “Pythia: Data Dependent Differentially Private Algorithm Selection”
    Ios Kotsogiannis, Ashwin Machanavajjhala, Gerome Miklau (UMass) and Michael Hay (Colgate), SIGMOD 2017
  2. “The cost of provable privacy: A case study on a national employee-employer dataset”
    Samuel Haney, Ashwin Machanavajjhala, John Abowd (US Census Bureau), Matthew Graham (US Census Bureau), Mark Kutzbach (US Census Bureau) and Lars Vihuber (Cornell), SIGMOD 2017
  3. “Directed Edge Recommendation Systems”,
    Ios Kotsogiannis, Elena Zheleva (Univ. Maryland, College Park), and Ashwin Machanavajjhala, WSDM 2017

2016


  1. “Differentially private regression diagnostics”,
    Yan Chen, Ashwin Machanavajjhala, Jerome Reiter (Stats, Duke) and Andres Barrientos (Stats, Duke), ICDM 2016
  2. 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, 2015.
  3. Sudeepa Roy, Laurel Orr, Dan Suciu: Explaining Query Answers with Explanation-Ready Databases. PVLDB 9(4): 348-359, 2015
  4. Zilong Tan, Shivnath Babu:
    Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases. PVLDB 9(10): 720-731, 2016.
  5. Brett Walenz and Jun Yang. “Perturbation analysis of database queries.” Proceedings of the VLDB Endowment, 9(14), 2016.

2015


  1. Machanavajjhala, Ashwin, and Daniel Kifer. “Designing statistical privacy for your data.” Communications of the ACM 58, no. 3 (2015): 58-67.
  2. He, Xi, Graham Cormode, Ashwin Machanavajjhala, Cecilia M. Procopiuc, and Divesh Srivastava. “DPT: differentially private trajectory synthesis using hierarchical reference systems.” Proceedings of the VLDB Endowment 8, no. 11 (2015): 1154-1165.
  3. Chen, Yan, and Ashwin Machanavajjhala. “On the Privacy Properties of Variants on the Sparse Vector Technique.” arXiv preprint arXiv:1508.07306(2015).
  4. Kunjir, Mayuresh, Brandon Fain, Kamesh Munagala, and Shivnath Babu. “ROBUS: Fair Cache Allocation for Multi-tenant Data-parallel Workloads.” arXiv preprint arXiv:1504.06736 (2015).
  5. You Wu, Boulos Harb, Jun Yang, and Cong Yu. 2015. Efficient evaluation of object-centric exploration queries for visualization. Proc. VLDB Endow. 8, 12 (August 2015), 1752-1763. DOI=http://dx.doi.org/10.14778/2824032.2824072

2014


  1. Huang, Botong, Nicholas WD Jarrett, Shivnath Babu, Sayan Mukherjee, and Jun Yang. “Cumulon: Cloud-Based Statistical Analysis from Users Perspective.” IEEE Data Eng. Bull. 37, no. 3 (2014): 77-89.
  2. Wu, You, Pankaj K. Agarwal, Chengkai Li, Jun Yang, and Cong Yu. “Toward computational fact-checking.” Proceedings of the VLDB Endowment 7, no. 7 (2014): 589-600.
  3. Sultana, Ayesha, Norfaeza Hassan, Chengkai Li, Jun Yang, and Cong Yu. “Incremental discovery of prominent situational facts.” In Data Engineering (ICDE), 2014 IEEE 30th International Conference on, pp. 112-123. IEEE, 2014.
  4. Kunjir, Mayuresh, Prajakta Kalmegh, and Shivnath Babu. “Thoth: Towards managing a multi-system cluster.” Proceedings of the VLDB Endowment 7, no. 13 (2014): 1689-1692.
  5. Lim, Harold, and Sarath Babu. “Execution and optimization of continuous windowed aggregation queries.” In Data Engineering Workshops (ICDEW), 2014 IEEE 30th International Conference on, pp. 303-309. IEEE, 2014.
  6. Kum, Hye-Chung, Ashok Krishnamurthy, Ashwin Machanavajjhala, Michael K. Reiter, and Stanley Ahalt. “Privacy preserving interactive record linkage (PPIRL).” Journal of the American Medical Informatics Association 21, no. 2 (2014): 212-220.
  7. Kifer, Daniel, and Ashwin Machanavajjhala. “Pufferfish: A framework for mathematical privacy definitions.” ACM Transactions on Database Systems (TODS) 39, no. 1 (2014): 3.
  8. Raval, Nisarg, Landon Cox, Animesh Srivastava, Ashwin Machanavajjhala, and Kiron Lebeck. “Markit: privacy markers for protecting visual secrets.” InProceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication, pp. 1289-1295. ACM, 2014.
  9. He, Xi, Ashwin Machanavajjhala, and Bolin Ding. “Blowfish privacy: Tuning privacy-utility trade-offs using policies.” In Proceedings of the 2014 ACM SIGMOD international conference on Management of data, pp. 1447-1458. ACM, 2014.
  10. Haney, Samuel, Ashwin Machanavajjhala, and Bolin Ding. “Answering Query Workloads with Optimal Error under Blowfish Privacy.” arXiv preprint arXiv:1404.3722 (2014).
  11. Stoddard, Ben, Yan Chen, and Ashwin Machanavajjhala. “Differentially Private Algorithms for Empirical Machine Learning.” arXiv preprint arXiv:1411.5428(2014).

2013


  1. Agarwal, Pankaj K., Lars Arge, Sathish Govindarajan, Jun Yang, and Ke Yi. “Efficient external memory structures for range-aggregate queries.”Computational Geometry 46, no. 3 (2013): 358-370.
  2. Thonangi, Risi, and Jun Yang. “Permuting data on random-access block storage.” Proceedings of the VLDB Endowment 6, no. 9 (2013): 721-732.
  3. Huang, Botong, 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, pp. 1-12. ACM, 2013.
  4. Herodotou, Herodotos, and Shivnath Babu. “A What-if Engine for Cost-based MapReduce Optimization.” IEEE Data Eng. Bull. 36, no. 1 (2013): 5-14.
  5. Babu, Shivnath, and Herodotos Herodotou. “Massively Parallel Databases and MapReduce Systems.” Foundations and Trends in Databases 5, no. 1 (2013): 1-104.
  6. Lim, Harold, Yuzhang Han, and Shivnath Babu. “How to Fit when No One Size Fits.” In CIDR, vol. 4, p. 35. 2013.
  7. Borisov, Nedyalko, and Shivnath Babu. “Rapid experimentation for testing and tuning a production database deployment.” In Proceedings of the 16th International Conference on Extending Database Technology, pp. 125-136. ACM, 2013.
  8. Aboulnaga, Ashraf, and Shivnath Babu. “Workload management for big data analytics.” In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 929-932. ACM, 2013.
  9. Lim, Harold, and Shivnath Babu. “Execution and optimization of continuous queries with cyclops.” In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 1069-1072. ACM, 2013.
  10. Rekatsinas, Theodoros, Amol Deshpande, and Ashwin Machanavajjhala. “SPARSI: partitioning sensitive data amongst multiple adversaries.”Proceedings of the VLDB Endowment 6, no. 13 (2013): 1594-1605.
  11. Chen, Jianjun, Ashwin Machanavajjhala, and George Varghese. “Scalable Social Coordination with Group Constraints using Enmeshed Queries.” In CIDR. 2013.
  12. Ryu, Eunsu, Yao Rong, Jie Li, and Ashwin Machanavajjhala. “curso: protect yourself from curse of attribute inference: a social network privacy-analyzer.” InProceedings of the ACM SIGMOD Workshop on Databases and Social Networks, pp. 13-18. ACM, 2013.
  13. Rastogi, Vibhor, Ashwin Machanavajjhala, Laukik Chitnis, and Akash Das Sarma. “Finding connected components in map-reduce in logarithmic rounds.” In Data Engineering (ICDE), 2013 IEEE 29th International Conference on, pp. 50-61. IEEE, 2013.
  14. Getoor, Lise, and Ashwin Machanavajjhala. “Entity resolution for big data.” InProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 1527-1527. ACM, 2013.
  15. Rekatsinas, Theodoros, Amol Deshpande, and Ashwin Machanavajjhala. “On Sharing Private Data with Multiple Non-Colluding Adversaries.” arXiv preprint arXiv:1302.6556 (2013).
  16. He, Xi, Ashwin Machanavajjhala, and Bolin Ding. “Blowfish privacy: Tuning privacy-utility trade-offs using policies.” In Proceedings of the 2014 ACM SIGMOD international conference on Management of data, pp. 1447-1458. ACM, 2014.