| Shared Arrangements: practical inter-query sharing for streaming dataflows. | 0 | 0.34 | 2020 |
| Megaphone: Latency-conscious state migration for distributed streaming dataflows. | 0 | 0.34 | 2019 |
| K-Pg: Shared State in Differential Dataflows. | 0 | 0.34 | 2018 |
| Latency-conscious dataflow reconfiguration | 0 | 0.34 | 2018 |
| Megaphone: latency-conscious state migration for distributed streaming dataflows | 2 | 0.42 | 2018 |
| Distributed Evaluation of Subgraph Queries Using Worst-case Optimal and Low-Memory Dataflows. | 0 | 0.34 | 2018 |
| Explaining Outputs in Modern Data Analytics. | 0 | 0.34 | 2016 |
| Faucet: a user-level, modular technique for flow control in dataflow engines. | 1 | 0.35 | 2016 |
| Explaining Outputs in Modern Data Analytics. | 9 | 0.44 | 2016 |
| Incremental, iterative data processing with timely dataflow. | 6 | 0.81 | 2016 |
| Scalability! but at what cost? | 3 | 0.39 | 2015 |
| Foundations of Differential Dataflow. | 0 | 0.34 | 2015 |
| Calibrating Data To Sensitivity In Private Data Analysis | 7 | 0.43 | 2014 |
| Calibrating Data to Sensitivity in Private Data Analysis. | 0 | 0.34 | 2014 |
| Differential Dataflow. | 0 | 0.34 | 2013 |
| Naiad: a timely dataflow system | 232 | 6.67 | 2013 |
| Formal Analysis of a Distributed Algorithm for Tracking Progress. | 3 | 0.55 | 2013 |
| A simple and practical algorithm for differentially private data release | 117 | 3.98 | 2012 |
| A workflow for differentially-private graph synthesis | 14 | 0.64 | 2012 |
| Managing large graphs on multi-cores with graph awareness | 23 | 1.13 | 2012 |
| Differential privacy with information flow control. | 1 | 0.37 | 2011 |
| Differential privacy with information flow control | 2 | 0.39 | 2011 |
| Differentially private combinatorial optimization | 47 | 2.21 | 2010 |
| Probabilistic Inference and Differential Privacy. | 10 | 0.72 | 2010 |
| A data-parallel toolkit for information retrieval | 1 | 0.36 | 2010 |
| Differentially-private network trace analysis | 54 | 2.19 | 2010 |
| Differentially Private Recommender Systems: Building Privacy into the Netflix Prize Contenders. | 37 | 1.52 | 2009 |
| Special Issue On The Thirty-Eighth Annual ACM Symposium On Theory Of Computing (STOC 2006) | 0 | 0.34 | 2009 |
| Privacy integrated queries: an extensible platform for privacy-preserving data analysis | 148 | 7.16 | 2009 |
| Differentially Private Approximation Algorithms | 10 | 1.09 | 2009 |
| Computing information retrieval performance measures efficiently in the presence of tied scores | 34 | 1.61 | 2008 |
| A decentralized algorithm for spectral analysis | 105 | 7.99 | 2008 |
| Privacy, accuracy, and consistency too: a holistic solution to contingency table release | 209 | 14.16 | 2007 |
| Mechanism Design via Differential Privacy | 590 | 25.28 | 2007 |
| Fast computation of low-rank matrix approximations | 42 | 4.44 | 2007 |
| The price of privacy and the limits of LP decoding | 64 | 8.00 | 2007 |
| Our data, ourselves: privacy via distributed noise generation | 215 | 12.66 | 2006 |
| Calibrating noise to sensitivity in private data analysis | 1007 | 49.75 | 2006 |
| Data Collection with Self-Enforcing Privacy | 18 | 1.33 | 2006 |
| Practical privacy: the SuLQ framework | 331 | 28.84 | 2005 |
| On Privacy-Preserving Histograms | 2 | 0.52 | 2005 |
| A first look at peer-to-peer worms: threats and defenses | 64 | 2.86 | 2005 |
| On profit-maximizing envy-free pricing | 149 | 10.00 | 2005 |
| Toward Privacy in Public Databases | 113 | 20.22 | 2005 |
| A uniform approach to accelerated PageRank computation | 47 | 2.98 | 2005 |
| On spectral learning of mixtures of distributions | 90 | 5.90 | 2005 |
| Spectral Analysis of Random Graphs with Skewed Degree Distributions | 25 | 1.38 | 2004 |
| Spectral Partitioning of Random Graphs | 242 | 15.51 | 2001 |
| Fast computation of low rank matrix | 20 | 7.33 | 2001 |
| Sampling Techniques for Kernel Methods | 62 | 7.98 | 2001 |
