Privid: Practical, Privacy-Preserving Video Analytics Queries | 0 | 0.34 | 2022 |
The Capacity of Causal Adversarial Channels. | 0 | 0.34 | 2022 |
Influencers and the Giant Component - The Fundamental Hardness in Privacy Protection for Socially Contagious Attributes. | 0 | 0.34 | 2021 |
Understanding Privacy-Utility Tradeoffs in Differentially Private Online Active Learning. | 0 | 0.34 | 2020 |
Tradeoffs for task parallelization in distributed optimization | 0 | 0.34 | 2014 |
A rate-disortion perspective on local differential privacy | 1 | 0.38 | 2014 |
Distributed Learning of Distributions via Social Sampling | 2 | 0.40 | 2013 |
Assisted sampling of correlated sources | 1 | 0.39 | 2013 |
Upper Bounds on the Capacity of Binary Channels With Causal Adversaries | 11 | 0.62 | 2013 |
Merging opinions by social sampling of posteriors | 0 | 0.34 | 2012 |
List-Decoding for the Arbitrarily Varying Channel Under State Constraints | 4 | 0.43 | 2012 |
Distributed learning from social sampling | 1 | 0.35 | 2012 |
Opinion dynamics and distributed learning of distributions | 8 | 0.68 | 2011 |
Coding against delayed adversaries | 9 | 0.70 | 2010 |
Randomization bounds on Gaussian arbitrarily varying channels | 4 | 0.43 | 2006 |
Fading observation alignment via feedback | 4 | 0.73 | 2005 |