Ashwin Machanavajjhala

160 papers A* 18A 7Misc 2Journal 95Unranked 32
YearRankTypeTitle / Venue / Authors
2025 J jnl
Differentially private explanations for aggregate query answers.
VLDB J.
Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy
2025 J jnl
PHSafe: Disclosure Avoidance for the 2020 Census Supplemental Demographic and Housing Characteristics File (S-DHC).
CoRR
William Sexton, Skye Berghel, Bayard Carlson, Samuel Haney, Luke Hartman, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Amritha Pai, Simran Rajpal, David Pujol, Ruchit Shrestha, Daniel Simmons-Marengo
2025 J jnl
R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys.
Commun. ACM
Wei Dong, Juanru Fang, Ke Yi, Yuchao Tao, Ashwin Machanavajjhala
2025 J jnl
SafeTab-H: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File B (Detailed DHC-B).
CoRR
William Sexton, Skye Berghel, Bayard Carlson, Samuel Haney, Luke Hartman, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Amritha Pai, Simran Rajpal, David Pujol, Ruchit Shrestha, Daniel Simmons-Marengo
2025 J jnl
SafeTab-P: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A).
CoRR
Samuel Haney, Skye Berghel, Bayard Carlson, Ryan Cumings-Menon, Luke Hartman, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Amritha Pai, Simran Rajpal, David Pujol, William Sexton, Ruchit Shrestha, Daniel Simmons-Marengo
2024 J jnl
Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys.
ACM Trans. Database Syst.
Wei Dong, Juanru Fang, Ke Yi, Yuchao Tao, Ashwin Machanavajjhala
2024 J jnl
Privately Answering Queries on Skewed Data via Per-Record Differential Privacy.
Proc. VLDB Endow.
Jeremy Seeman, William Sexton, David Pujol, Ashwin Machanavajjhala
2024 J jnl
Slowly Scaling Per-Record Differential Privacy.
CoRR
Brian Finley, Anthony M. Caruso, Justin C. Doty, Ashwin Machanavajjhala, Mikaela R. Meyer, David Pujol, William Sexton, Zachary Terner
2023 J jnl
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms.
CoRR
Shweta Patwa, Danyu Sun, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy
2023 J jnl
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms.
Proc. VLDB Endow.
Shweta Patwa, Danyu Sun, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy
2023 J jnl
Explaining Differentially Private Query Results With DPXPlain.
Proc. VLDB Endow.
Tingyu Wang, Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy
2023 J jnl
Longshot: Indexing Growing Databases using MPC and Differential Privacy.
Proc. VLDB Endow.
Yanping Zhang, Johes Bater, Kartik Nayak, Ashwin Machanavajjhala
2023 J jnl
Optimizing Error of High-Dimensional Statistical Queries Under Differential Privacy.
J. Priv. Confidentiality
Ryan McKenna, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
2023 J jnl
PreFair: Privately Generating Justifiably Fair Synthetic Data.
Proc. VLDB Endow.
David Pujol, Amir Gilad, Ashwin Machanavajjhala
2023 A* conf
Private Proof-of-Stake Blockchains using Differentially-Private Stake Distortion.
USENIX Security Symposium
Chenghong Wang, David Pujol, Kartik Nayak, Ashwin Machanavajjhala
2023 J jnl
Private Proof-of-Stake Blockchains using Differentially-private Stake Distortion.
IACR Cryptol. ePrint Arch.
Chenghong Wang, David Pujol, Kartik Nayak, Ashwin Machanavajjhala
2023 J jnl
Privately Answering Queries on Skewed Data via Per Record Differential Privacy.
CoRR
Jeremy Seeman, William Sexton, David Pujol, Ashwin Machanavajjhala
2023 J jnl
Publishing Wikipedia usage data with strong privacy guarantees.
CoRR
Temilola Adeleye, Skye Berghel, Damien Desfontaines, Michael Hay, Isaac Johnson, Cléo Lemoisson, Ashwin Machanavajjhala, Tom Magerlein, Gabriele Modena, David Pujol, Daniel Simmons-Marengo, Hal Triedman
2023 J jnl
R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys.
SIGMOD Rec.
Wei Dong, Juanru Fang, Ke Yi, Yuchao Tao, Ashwin Machanavajjhala
2022 J jnl
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census.
CoRR
Daniel Kifer, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Philip Leclerc, Ashwin Machanavajjhala, William Sexton, Pavel Zhuravlev
2022 J jnl
DPXPlain: Privately Explaining Aggregate Query Answers.
CoRR
Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy
2022 J jnl
DPXPlain: Privately Explaining Aggregate Query Answers.
Proc. VLDB Endow.
Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala, Sudeepa Roy
2022 — conf
IncShrink: Architecting Efficient Outsourced Databases using Incremental MPC and Differential Privacy.
SIGMOD Conference
Chenghong Wang, Johes Bater, Kartik Nayak, Ashwin Machanavajjhala
2022 J jnl
IncShrink: Architecting Efficient Outsourced Databases using Incremental MPC and Differential Privacy.
CoRR
Chenghong Wang, Johes Bater, Kartik Nayak, Ashwin Machanavajjhala
2022 J jnl
Multi-Analyst Differential Privacy for Online Query Answering.
CoRR
David Pujol, Albert Sun, Brandon Fain, Ashwin Machanavajjhala
2022 J jnl
Multi-Analyst Differential Privacy for Online Query Answering.
Proc. VLDB Endow.
David Pujol, Albert Sun, Brandon Fain, Ashwin Machanavajjhala
2022 J jnl
PreFair: Privately Generating Justifiably Fair Synthetic Data.
CoRR
David Pujol, Amir Gilad, Ashwin Machanavajjhala
2022 — conf
R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys.
SIGMOD Conference
Wei Dong, Juanru Fang, Ke Yi, Yuchao Tao, Ashwin Machanavajjhala
2022 J jnl
The 2020 Census Disclosure Avoidance System TopDown Algorithm.
CoRR
John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Micah Heineck, Christine Heiss, Robert Johns, Daniel Kifer, Philip Leclerc, Ashwin Machanavajjhala, Brett Moran, William Sexton, Matthew Spence, Pavel Zhuravlev
2022 J jnl
Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy.
CoRR
Skye Berghel, Philip Bohannon, Damien Desfontaines, Charles Estes, Samuel Haney, Luke Hartman, Michael Hay, Ashwin Machanavajjhala, Tom Magerlein, Gerome Miklau, Amritha Pai, William Sexton, Ruchit Shrestha
2021 J jnl
Benchmarking Differentially Private Synthetic Data Generation Algorithms.
CoRR
Yuchao Tao, Ryan McKenna, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
2021 J jnl
Budget Sharing for Multi-Analyst Differential Privacy.
Proc. VLDB Endow.
David Pujol, Yikai Wu, Brandon Fain, Ashwin Machanavajjhala
2021 — conf
DP-Sync: Hiding Update Patterns in Secure Outsourced Databases with Differential Privacy.
SIGMOD Conference
Chenghong Wang, Johes Bater, Kartik Nayak, Ashwin Machanavajjhala
2021 J jnl
DP-Sync: Hiding Update Patterns in Secure Outsourced Databases with Differential Privacy.
CoRR
Chenghong Wang, Johes Bater, Kartik Nayak, Ashwin Machanavajjhala
2021 J jnl
DP-cryptography: marrying differential privacy and cryptography in emerging applications.
Commun. ACM
Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal
2021 J jnl
Differentially Private Algorithms for 2020 Census Detailed DHC Race \& Ethnicity.
CoRR
Samuel Haney, William Sexton, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
2021 J jnl
Equity and Privacy: More Than Just a Tradeoff.
CoRR
David Pujol, Ashwin Machanavajjhala
2021 J jnl
Equity and Privacy: More Than Just a Tradeoff.
IEEE Secur. Priv.
David Pujol, Ashwin Machanavajjhala
2021 J jnl
HDMM: Optimizing error of high-dimensional statistical queries under differential privacy.
CoRR
Ryan McKenna, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
2021 — conf
Practical Security and Privacy for Database Systems.
SIGMOD Conference
Xi He, Jennie Rogers, Johes Bater, Ashwin Machanavajjhala, Chenghong Wang, Xiao Wang
2021 J jnl
Prior-Aware Distribution Estimation for Differential Privacy.
CoRR
Yuchao Tao, Johes Bater, Ashwin Machanavajjhala
2021 — conf
Synthesizing Linked Data Under Cardinality and Integrity Constraints.
SIGMOD Conference
Amir Gilad, Shweta Patwa, Ashwin Machanavajjhala
2021 J jnl
Synthesizing Linked Data Under Cardinality and Integrity Constraints.
CoRR
Amir Gilad, Shweta Patwa, Ashwin Machanavajjhala
2020 J jnl
Budget Sharing for Multi-Analyst Differential Privacy.
CoRR
David Pujol, Yikai Wu, Brandon Fain, Ashwin Machanavajjhala
2020 — conf
Computing Local Sensitivities of Counting Queries with Joins.
SIGMOD Conference
Yuchao Tao, Xi He, Ashwin Machanavajjhala, Sudeepa Roy
2020 J jnl
Computing Local Sensitivities of Counting Queries with Joins.
CoRR
Yuchao Tao, Xi He, Ashwin Machanavajjhala, Sudeepa Roy
2020 — conf
Crypt?: Crypto-Assisted Differential Privacy on Untrusted Servers.
SIGMOD Conference
Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha
2020 J jnl
DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications.
CoRR
Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal
2020 — conf
Fair decision making using privacy-protected data.
FAT*
David Pujol, Ryan McKenna, Satya Kuppam, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
2020 A* conf
One-sided Differential Privacy.
ICDE
Ios Kotsogiannis, Stelios Doudalis, Samuel Haney, Ashwin Machanavajjhala, Sharad Mehrotra
2020 Misc conf
Poirot: private contact summary aggregation: poster abstract.
SenSys
Yanping Zhang, Chenghong Wang, David Pujol, Johes Bater, Matthew Lentz, Ashwin Machanavajjhala, Kartik Nayak, Lavanya Vasudevan, Jun Yang
2020 J jnl
ϵKTELO: A Framework for Defining Differentially Private Computations.
ACM Trans. Database Syst.
Dan Zhang, Ryan McKenna, Ios Kotsogiannis, George Bissias, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
2019 J jnl
#8712;: A Framework for Defining Differentially-Private Computations.
SIGMOD Rec.
Dan Zhang, Ryan McKenna, Ios Kotsogiannis, George Bissias, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
2019 — conf
APEx: Accuracy-Aware Differentially Private Data Exploration.
SIGMOD Conference
Chang Ge, Xi He, Ihab F. Ilyas, Ashwin Machanavajjhala
2019 J jnl
Answering Summation Queries for Numerical Attributes under Differential Privacy.
CoRR
Yikai Wu, David Pujol, Ios Kotsogiannis, Ashwin Machanavajjhala
2019 A conf
Architecting a Differentially Private SQL Engine.
CIDR
Ios Kotsogiannis, Yuchao Tao, Ashwin Machanavajjhala, Gerome Miklau, Michael Hay
2019 A* conf
Capacity Bounded Differential Privacy.
NeurIPS
Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala
2019 J jnl
Capacity Bounded Differential Privacy.
CoRR
Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala
2019 J jnl
Fair Decision Making using Privacy-Protected Data.
CoRR
Satya Kuppam, Ryan McKenna, David Pujol, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
2019 J jnl
Olympus: Sensor Privacy through Utility Aware Obfuscation.
Proc. Priv. Enhancing Technol.
Nisarg Raval, Ashwin Machanavajjhala, Jerry Pan
2019 J jnl
Outis: Crypto-Assisted Differential Privacy on Untrusted Servers.
CoRR
Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha
2019 J jnl
PSynDB: Accurate and Accessible Private Data Generation.
Proc. VLDB Endow.
Zhiqi Huang, Ryan McKenna, George Bissias, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
2019 A conf
Permissions Plugins as Android Apps.
MobiSys
Nisarg Raval, Ali Razeen, Ashwin Machanavajjhala, Landon P. Cox, Andrew Warfield
2019 — conf
PrivStream: Differentially Private Event Detection on Data Streams.
CODASPY
Maryam Fanaeepour, Ashwin Machanavajjhala
2019 — conf
Privacy Changes Everything.
Poly/DMAH@VLDB
Jennie Rogers, Johes Bater, Xi He, Ashwin Machanavajjhala, Madhav Suresh, Xiao Wang
2019 J jnl
PrivateSQL: A Differentially Private SQL Query Engine.
Proc. VLDB Endow.
Ios Kotsogiannis, Yuchao Tao, Xi He, Maryam Fanaeepour, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
2019 J jnl
Releasing Earnings Distributions using Differential Privacy - Disclosure Avoidance System For Post-Secondary Employment Outcomes (PSEO).
J. Priv. Confidentiality
Andrew David Foote, Ashwin Machanavajjhala, Kevin McKinney
2018 — ch.
Analyzing Your Location Data with Provable Privacy Guarantees.
Handbook of Mobile Data Privacy
Ashwin Machanavajjhala, Xi He
2018 J jnl
Differentially Private Hierarchical Count-of-Counts Histograms.
Proc. VLDB Endow.
Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala
2018 J jnl
Differentially Private Hierarchical Group Size Estimation.
CoRR
Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala
2018 — conf
EKTELO: A Framework for Defining Differentially-Private Computations.
SIGMOD Conference
Dan Zhang, Ryan McKenna, Ios Kotsogiannis, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
2018 J jnl
Ektelo: A Framework for Defining Differentially-Private Computations.
CoRR
Dan Zhang, Ryan McKenna, Ios Kotsogiannis, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
2018 — conf
IoT-Detective: Analyzing IoT Data Under Differential Privacy.
SIGMOD Conference
Sameera Ghayyur, Yan Chen, Roberto Yus, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau, Sharad Mehrotra
2018 J jnl
Is my model any good: differentially private regression diagnostics.
Knowl. Inf. Syst.
Yan Chen, Andrés F. Barrientos, Ashwin Machanavajjhala, Jerome P. Reiter
2018 J jnl
Optimizing error of high-dimensional statistical queries under differential privacy.
CoRR
Ryan McKenna, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
2018 J jnl
Optimizing error of high-dimensional statistical queries under differential privacy.
Proc. VLDB Endow.
Ryan McKenna, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
2018 — ch.
Randomization Methods to Ensure Data Privacy.
Encyclopedia of Database Systems (2nd ed.)
Ashwin Machanavajjhala, Johannes Gehrke
2018 J jnl
ShrinkWrap: Efficient SQL Query Processing in Differentially Private Data Federations.
Proc. VLDB Endow.
Johes Bater, Xi He, William Ehrich, Ashwin Machanavajjhala, Jennie Rogers
2018 J jnl
Shrinkwrap: Differentially-Private Query Processing in Private Data Federations.
CoRR
Johes Bater, Xi He, William Ehrich, Ashwin Machanavajjhala, Jennie Rogers
2017 A* conf
Composing Differential Privacy and Secure Computation: A Case Study on Scaling Private Record Linkage.
CCS
Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava
2017 — conf
DIAS: Differentially Private Interactive Algorithm Selection using Pythia.
SIGMOD Conference
Ios Kotsogiannis, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Margaret Orr
2017 — conf
Differential Privacy in the Wild: A Tutorial on Current Practices & Open Challenges.
SIGMOD Conference
Ashwin Machanavajjhala, Xi He, Michael Hay
2017 A conf
Directed Edge Recommender System.
WSDM
Ios Kotsogiannis, Elena Zheleva, Ashwin Machanavajjhala
2017 J jnl
One-sided Differential Privacy.
CoRR
Stelios Doudalis, Ios Kotsogiannis, Samuel Haney, Ashwin Machanavajjhala, Sharad Mehrotra
2017 A* conf
PeGaSus: Data-Adaptive Differentially Private Stream Processing.
CCS
Yan Chen, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
2017 J jnl
Privacy-Preserving Data Analysis for the Federal Statistical Agencies.
CoRR
John M. Abowd, Lorenzo Alvisi, Cynthia Dwork, Sampath Kannan, Ashwin Machanavajjhala, Jerome P. Reiter
2017 J jnl
Private Exploration Primitives for Data Cleaning.
CoRR
Chang Ge, Ihab F. Ilyas, Xi He, Ashwin Machanavajjhala
2017 — conf
Protecting Visual Secrets Using Adversarial Nets.
CVPR Workshops
Nisarg Raval, Ashwin Machanavajjhala, Landon P. Cox
2017 — conf
Pythia: Data Dependent Differentially Private Algorithm Selection.
SIGMOD Conference
Ios Kotsogiannis, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
2017 J jnl
Scaling Private Record Linkage using Output Constrained Differential Privacy.
CoRR
Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava
2017 — conf
Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics.
SIGMOD Conference
Samuel Haney, Ashwin Machanavajjhala, John M. Abowd, Matthew Graham, Mark Kutzbach, Lars Vilhuber
2017 Misc conf
ePrivateeye: to the edge and beyond!
SEC
Christopher Streiffer, Animesh Srivastava, Victor Orlikowski, Yesenia Velasco, Vincentius Martin, Nisarg Raval, Ashwin Machanavajjhala, Landon P. Cox
2016 J jnl
A Demonstration of VisDPT: Visual Exploration of Differentially Private Trajectories.
Proc. VLDB Endow.
Xi He, Nisarg Raval, Ashwin Machanavajjhala
2016 — conf
Ayumu: Efficient lifelogging with focused tasks.
MobiCASE
Benjamin Stoddard, Kate O'Hanlon, Brian Lin, Ashwin Machanavajjhala, Landon P. Cox
2016 — conf
Demo: What You Mark is What Apps See.
MobiSys (Companion Volume)
Nisarg Raval, Animesh Srivastava, Ali Razeen, Kiron Lebeck, Ashwin Machanavajjhala, Landon P. Cox
2016 J jnl
Differential Privacy in the Wild: A tutorial on current practices & open challenges.
Proc. VLDB Endow.
Ashwin Machanavajjhala, Xi He, Michael Hay
2016 A* conf
Differentially Private Regression Diagnostics.
ICDM
Yan Chen, Ashwin Machanavajjhala, Jerome P. Reiter, Andrés F. Barrientos
2016 — conf
Exploring Privacy-Accuracy Tradeoffs using DPComp.
SIGMOD Conference
Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang, George Bissias
2016 — conf
Principled Evaluation of Differentially Private Algorithms using DPBench.
SIGMOD Conference
Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang
2016 A conf
What You Mark is What Apps See.
MobiSys
Nisarg Raval, Animesh Srivastava, Ali Razeen, Kiron Lebeck, Ashwin Machanavajjhala, Landon P. Cox
2015 J jnl
DPT: Differentially Private Trajectory Synthesis Using Hierarchical Reference Systems.
Proc. VLDB Endow.
Xi He, Graham Cormode, Ashwin Machanavajjhala, Cecilia M. Procopiuc, Divesh Srivastava
2015 J jnl
Design of Policy-Aware Differentially Private Algorithms.
Proc. VLDB Endow.
Samuel Haney, Ashwin Machanavajjhala, Bolin Ding
2015 J jnl
Designing statistical privacy for your data.
Commun. ACM
Ashwin Machanavajjhala, Daniel Kifer
2015 J jnl
On the Privacy Properties of Variants on the Sparse Vector Technique.
CoRR
Yan Chen, Ashwin Machanavajjhala
2015 J jnl
Principled Evaluation of Differentially Private Algorithms using DPBench.
CoRR
Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang
2014 J jnl
Answering Query Workloads with Optimal Error under Blowfish Privacy.
CoRR
Samuel Haney, Ashwin Machanavajjhala, Bolin Ding
2014 — conf
Blowfish privacy: tuning privacy-utility trade-offs using policies.
SIGMOD Conference
Xi He, Ashwin Machanavajjhala, Bolin Ding
2014 J jnl
Differentially Private Algorithms for Empirical Machine Learning.
CoRR
Ben Stoddard, Yan Chen, Ashwin Machanavajjhala
2014 — conf
MarkIt: privacy markers for protecting visual secrets.
UbiComp Adjunct
Nisarg Raval, Landon P. Cox, Animesh Srivastava, Ashwin Machanavajjhala, Kiron Lebeck
2014 J jnl
Privacy preserving interactive record linkage (PPIRL).
J. Am. Medical Informatics Assoc.
Hye-Chung Kum, Ashok K. Krishnamurthy, Ashwin Machanavajjhala, Michael K. Reiter, Stanley C. Ahalt
2014 J jnl
Pufferfish: A framework for mathematical privacy definitions.
ACM Trans. Database Syst.
Daniel Kifer, Ashwin Machanavajjhala
2014 J jnl
Social Genome: Putting Big Data to Work for Population Informatics.
Computer
Hye-Chung Kum, Ashok Kumar Krishnamurthy, Ashwin Machanavajjhala, Stanley C. Ahalt
2013 J jnl
A SPARSI: Partitioning Sensitive Data amongst Multiple Adversaries.
Proc. VLDB Endow.
Theodoros Rekatsinas, Amol Deshpande, Ashwin Machanavajjhala
2013 J jnl
Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies.
CoRR
Xi He, Ashwin Machanavajjhala, Bolin Ding
2013 A* conf
Entity resolution for big data.
KDD
Lise Getoor, Ashwin Machanavajjhala
2013 A* conf
Finding connected components in map-reduce in logarithmic rounds.
ICDE
Vibhor Rastogi, Ashwin Machanavajjhala, Laukik Chitnis, Anish Das Sarma
2013 A* conf
Network sampling.
KDD
Lise Getoor, Ashwin Machanavajjhala
2013 J jnl
On Sharing Private Data with Multiple Non-Colluding Adversaries
CoRR
Theodoros Rekatsinas, Amol Deshpande, Ashwin Machanavajjhala
2013 — ed.
Proceedings of the 3rd ACM SIGMOD Workshop on Databases and Social Networks, DBSocial 2013, New York, NY, USA, June, 23, 2013
DBSocial
Kristen LeFevre, Ashwin Machanavajjhala, Adam Silberstein
2013 A conf
Scalable Social Coordination with Group Constraints using Enmeshed Queries.
CIDR
Jianjun Chen, Ashwin Machanavajjhala, George Varghese
2013 J jnl
WOO: A Scalable and Multi-tenant Platform for Continuous Knowledge Base Synthesis.
Proc. VLDB Endow.
Kedar Bellare, Carlo Curino, Ashwin Machanavajjhala, Peter Mika, Mandar Rahurkar, Aamod Sane
2013 — conf
curso: protect yourself from curse of attribute inference: a social network privacy-analyzer.
DBSocial
Eunsu Ryu, Yao Rong, Jie Li, Ashwin Machanavajjhala
2012 A* conf
A rigorous and customizable framework for privacy.
PODS
Daniel Kifer, Ashwin Machanavajjhala
2012 J jnl
An Analysis of Structured Data on the Web
CoRR
Nilesh N. Dalvi, Ashwin Machanavajjhala, Bo Pang
2012 J jnl
An Analysis of Structured Data on the Web.
Proc. VLDB Endow.
Nilesh N. Dalvi, Ashwin Machanavajjhala, Bo Pang
2012 A conf
An automatic blocking mechanism for large-scale de-duplication tasks.
CIKM
Anish Das Sarma, Ankur Jain, Ashwin Machanavajjhala, Philip Bohannon
2012 J jnl
Big privacy: protecting confidentiality in big data.
XRDS
Ashwin Machanavajjhala, Jerome P. Reiter
2012 — conf
Challenges in enabling social application at scale: cloudDB'12 invited-keynote talk abstract.
CloudDB@CIKM
Ashwin Machanavajjhala
2012 J jnl
Entity Resolution: Theory, Practice & Open Challenges.
Proc. VLDB Endow.
Lise Getoor, Ashwin Machanavajjhala
2012 J jnl
Finding Connected Components on Map-reduce in Logarithmic Rounds
CoRR
Vibhor Rastogi, Ashwin Machanavajjhala, Laukik Chitnis, Anish Das Sarma
2012 A* conf
Information integration over time in unreliable and uncertain environments.
WWW
Aditya Pal, Vibhor Rastogi, Ashwin Machanavajjhala, Philip Bohannon
2012 J jnl
Publishing Search Logs - A Comparative Study of Privacy Guarantees.
IEEE Trans. Knowl. Data Eng.
Michaela Götz, Ashwin Machanavajjhala, Guozhang Wang, Xiaokui Xiao, Johannes Gehrke
2012 J jnl
Scalable Social Coordination using Enmeshed Queries
CoRR
Jianjun Chen, Ashwin Machanavajjhala, George Varghese
2011 J jnl
CBLOCK: An Automatic Blocking Mechanism for Large-Scale De-duplication Tasks
CoRR
Anish Das Sarma, Ankur Jain, Ashwin Machanavajjhala, Philip Bohannon
2011 A conf
Collective extraction from heterogeneous web lists.
WSDM
Ashwin Machanavajjhala, Arun Shankar Iyer, Philip Bohannon, Srujana Merugu
2011 — ch.
E-Privacy.
Encyclopedia of Cryptography and Security (2nd Ed.)
Johannes Gehrke, Ashwin Machanavajjhala
2011 — conf
Feed following: the big data challenge in social applications.
DBSocial
Adam Silberstein, Ashwin Machanavajjhala, Raghu Ramakrishnan
2011 A* conf
Highly efficient algorithms for structural clustering of large websites.
WWW
Lorenzo Blanco, Nilesh N. Dalvi, Ashwin Machanavajjhala
2011 J jnl
Load Balancing and Range Queries in P2P Systems Using P-Ring.
ACM Trans. Internet Techn.
Adina Crainiceanu, Prakash Linga, Ashwin Machanavajjhala, Johannes Gehrke, Jayavel Shanmugasundaram
2011 — conf
No free lunch in data privacy.
SIGMOD Conference
Daniel Kifer, Ashwin Machanavajjhala
2011 J jnl
Personalized Social Recommendations - Accurate or Private?
CoRR
Ashwin Machanavajjhala, Aleksandra Korolova, Atish Das Sarma
2011 J jnl
Personalized Social Recommendations - Accurate or Private?
Proc. VLDB Endow.
Ashwin Machanavajjhala, Aleksandra Korolova, Atish Das Sarma
2011 A* conf
Sampling hidden objects using nearest-neighbor oracles.
KDD
Nilesh N. Dalvi, Ravi Kumar, Ashwin Machanavajjhala, Vibhor Rastogi
2010 J jnl
On the (Im)possibility of Preserving Utility and Privacy in Personalized Social Recommendations.
CoRR
Ashwin Machanavajjhala, Aleksandra Korolova, Atish Das Sarma
2010 A* conf
Privacy in data publishing.
ICDE
Johannes Gehrke, Daniel Kifer, Ashwin Machanavajjhala
2009 J jnl
Data Publishing against Realistic Adversaries.
Proc. VLDB Endow.
Ashwin Machanavajjhala, Johannes Gehrke, Michaela Götz
2009 J jnl
Privacy in Search Logs
CoRR
Michaela Götz, Ashwin Machanavajjhala, Guozhang Wang, Xiaokui Xiao, Johannes Gehrke
2009 J jnl
Privacy-Preserving Data Publishing.
Found. Trends Databases
Bee-Chung Chen, Daniel Kifer, Kristen LeFevre, Ashwin Machanavajjhala
2009 — ch.
Randomization Methods to Ensure Data Privacy.
Encyclopedia of Database Systems
Ashwin Machanavajjhala, Johannes Gehrke
2008 — —
Defining and Enforcing Privacy in Data Sharing.
Ashwin Machanavajjhala
2008 A* conf
Privacy: Theory meets Practice on the Map.
ICDE
Ashwin Machanavajjhala, Daniel Kifer, John M. Abowd, Johannes Gehrke, Lars Vilhuber
2008 J jnl
Scalable ranked publish/subscribe.
Proc. VLDB Endow.
Ashwin Machanavajjhala, Erik Vee, Minos N. Garofalakis, Jayavel Shanmugasundaram
2007 — conf
P-ring: an efficient and robust P2P range index structure.
SIGMOD Conference
Adina Crainiceanu, Prakash Linga, Ashwin Machanavajjhala, Johannes Gehrke, Jayavel Shanmugasundaram
2007 J jnl
Worst-Case Background Knowledge for Privacy-Preserving Data Publishing
CoRR
David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke, Joseph Y. Halpern
2007 A* conf
Worst-Case Background Knowledge for Privacy-Preserving Data Publishing.
ICDE
David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke, Joseph Y. Halpern
2006 A* conf
On the efficiency of checking perfect privacy.
PODS
Ashwin Machanavajjhala, Johannes Gehrke
2006 — conf
Trusted CVS.
ICDE Workshops
Muthuramakrishnan Venkitasubramaniam, Ashwin Machanavajjhala, David J. Martin, Johannes Gehrke
2006 A* conf
l-Diversity: Privacy Beyond k-Anonymity.
ICDE
Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer, Muthuramakrishnan Venkitasubramaniam
2004 — conf
A storage and indexing framework for p2p systems.
WWW (Alternate Track Papers & Posters)
Adina Crainiceanu, Prakash Linga, Ashwin Machanavajjhala, Johannes Gehrke, Jayavel Shanmugasundaram
2004 — conf
An Indexing Framework for Peer-to-Peer Systems.
SIGMOD Conference
Adina Crainiceanu, Prakash Linga, Ashwin Machanavajjhala, Johannes Gehrke, Jayavel Shanmugasundaram