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    Author information
    First name: Ashwin
    Last name: Machanavajjhala
    DBLP: m/AMachanavajjhala
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    Below you find the publications which have been written by this author.

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    Conference paper
    John M. Abowd, Lorenzo Alvisi, Cynthia Dwork, Sampath Kannan, Ashwin Machanavajjhala, Jerome P. Reiter.
    Privacy-Preserving Data Analysis for the Federal Statistical Agencies.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Ios Kotsogiannis, Elena Zheleva, Ashwin Machanavajjhala.
    Directed Edge Recommender System.
    Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, WSDM 2017, Cambridge, United Kingdom, February 6-10, 2017 2017 (0) 2017
    Conference paper
    Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava.
    Scaling Private Record Linkage using Output Constrained Differential Privacy.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Ios Kotsogiannis, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau.
    Pythia: Data Dependent Differentially Private Algorithm Selection.
    Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14-19, 2017 2017 (0) 2017
    Conference paper
    Ashwin Machanavajjhala, Xi He, Michael Hay.
    Differential Privacy in the Wild: A Tutorial on Current Practices Open Challenges.
    Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14-19, 2017 2017 (0) 2017
    Conference paper
    Ios Kotsogiannis, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Margaret Orr.
    DIAS: Differentially Private Interactive Algorithm Selection using Pythia.
    Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14-19, 2017 2017 (0) 2017
    Conference paper
    Samuel Haney, Ashwin Machanavajjhala, John M. Abowd, Matthew Graham, Mark Kutzbach, Lars Vilhuber.
    Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics.
    Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14-19, 2017 2017 (0) 2017
    Conference paper
    Nisarg Raval, Ashwin Machanavajjhala, Landon P. Cox.
    Protecting Visual Secrets Using Adversarial Nets.
    2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops, Honolulu, HI, USA, July 21-26, 2017 2017 (0) 2017
    Conference paper
    Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava.
    Composing Differential Privacy and Secure Computation: A Case Study on Scaling Private Record Linkage.
    Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017, Dallas, TX, USA, October 30 - November 03, 2017 2017 (0) 2017
    Conference paper
    Yan Chen, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau.
    PeGaSus: Data-Adaptive Differentially Private Stream Processing.
    Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017, Dallas, TX, USA, October 30 - November 03, 2017 2017 (0) 2017
    Conference paper
    Christopher Streiffer, Animesh Srivastava, Victor Orlikowski, Yesenia Velasco, Vincentius Martin, Nisarg Raval, Ashwin Machanavajjhala, Landon P. Cox.
    ePrivateeye: to the edge and beyond!
    Proceedings of the Second ACM/IEEE Symposium on Edge Computing, San Jose / Silicon Valley, SEC 2017, CA, USA, October 12-14, 2017 2017 (0) 2017
    Conference paper
    Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang, George Bissias.
    Exploring Privacy-Accuracy Tradeoffs using DPComp.
    Proceedings of the 2016 International Conference on Management of Data, SIGMOD Conference 2016, San Francisco, CA, USA, June 26 - July 01, 2016 2016 (0) 2016
    Conference paper
    Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang.
    Principled Evaluation of Differentially Private Algorithms using DPBench.
    Proceedings of the 2016 International Conference on Management of Data, SIGMOD Conference 2016, San Francisco, CA, USA, June 26 - July 01, 2016 2016 (0) 2016
    Conference paper
    Nisarg Raval, Animesh Srivastava, Ali Razeen, Kiron Lebeck, Ashwin Machanavajjhala, Landon P. Cox.
    What You Mark is What Apps See.
    Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2016, Singapore, June 26-30, 2016 2016 (0) 2016
    Conference paper
    Nisarg Raval, Animesh Srivastava, Ali Razeen, Kiron Lebeck, Ashwin Machanavajjhala, Landon P. Cox.
    Demo: What You Mark is What Apps See.
    Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion, Singapore, Singapore, June 25-30, 2016 2016 (0) 2016
    Conference paper
    Ashwin Machanavajjhala, Xi He, Michael Hay.
    Differential Privacy in the Wild: A tutorial on current practices open challenges.
    PVLDB 2015, Volume 9 (0) 2016
    Conference paper
    Xi He, Nisarg Raval, Ashwin Machanavajjhala.
    A Demonstration of VisDPT: Visual Exploration of Differentially Private Trajectories.
    PVLDB 2015, Volume 9 (0) 2016
    Conference paper
    Yan Chen, Ashwin Machanavajjhala, Jerome P. Reiter, Andrés F. Barrientos.
    Differentially Private Regression Diagnostics.
    IEEE 16th International Conference on Data Mining, ICDM 2016, December 12-15, 2016, Barcelona, Spain 2016 (0) 2016
    Conference paper
    Ashwin Machanavajjhala, Daniel Kifer.
    Designing statistical privacy for your data.
    Commun. ACM 2015, Volume 58 (0) 2015
    Conference paper
    Xi He, Graham Cormode, Ashwin Machanavajjhala, Cecilia M. Procopiuc, Divesh Srivastava.
    DPT: Differentially Private Trajectory Synthesis Using Hierarchical Reference Systems.
    PVLDB 2014, Volume 8 (0) 2015
    Journal article
    Yan Chen, Ashwin Machanavajjhala.
    On the Privacy Properties of Variants on the Sparse Vector Technique.
    CoRR 2015, Volume 0 (0) 2015
    Conference paper
    Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang.
    Principled Evaluation of Differentially Private Algorithms using DPBench.
    CoRR 2015, Volume 0 (0) 2015
    Conference paper
    Samuel Haney, Ashwin Machanavajjhala, Bolin Ding.
    Design of Policy-Aware Differentially Private Algorithms.
    PVLDB 2015, Volume 9 (0) 2015
    Journal article
    Daniel Kifer, Ashwin Machanavajjhala.
    Pufferfish: A framework for mathematical privacy definitions.
    ACM Trans. Database Syst. 2014, Volume 39 (0) 2014
    Journal article
    Hye-Chung Kum, Ashok Krishnamurthy, Ashwin Machanavajjhala, Stanley C. Ahalt.
    Social Genome: Putting Big Data to Work for Population Informatics.
    IEEE Computer 2014, Volume 47 (0) 2014
    Show item 1 to 25 of 80  

    Your query returned 80 matches in the database.