PANEL: Statistical Theory, Privacy and Data Analysis

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=GJXiYzi8KRc


Duration: 1:00:02
1,070 views
15

‹ Home ‹ Programs & Events ‹ Workshops & Symposia ‹ Privacy and the Science of Data Analysis
Primary tabs
View (active tab)
Edit
Clone content
Talks Spring 2019

PANEL: Statistical Theory, Privacy and Data Analysis
Tuesday, April 9th, 2019 4:15 pm – 5:30 pm
Add to Calendar
Event: Privacy and the Science of Data Analysis
Speaker:
Moderator: Aleksandra Slavkovic (Pennsylvania State University) ||| Panelists: Anand Sarwate (Rutgers University), Thomas Steinke (IBM Almaden), Bin Yu (UC Berkeley), John Duchi (Stanford University), and Yu-Xiang Wang (UC Santa Barbara)
Privacy and the Science of Data Analysis
https://simons.berkeley.edu/talks/panel-statistical-theory-privacy-and-data-analysis



Other Videos By Simons Institute for the Theory of Computing


2019-04-11Private Meta-Selection
2019-04-11Private Boosting and Noise-tolerant Learning
2019-04-11Privacy Amplification by Sampling and Renyi Differential Privacy
2019-04-11Locally Private Statistical Inference: Communication, Samples, and Shared Randomness
2019-04-10Open Problem Session
2019-04-10The Privacy Blanket of the Shuffle Model
2019-04-10Black-box Random Differential Privacy with Sensitivity Sampling
2019-04-10Pufferfish Privacy Mechanisms for Correlated Data
2019-04-10Bandit Learning under Differential Privacy
2019-04-10Differentially Private Change-Point Detection
2019-04-09PANEL: Statistical Theory, Privacy and Data Analysis
2019-04-09Optimality in Locally Private Estimation and Learning
2019-04-09Node Privacy, High-dimensional Graph Summaries, and Block Models
2019-04-09Differentially Private Inference for Regression Coefficients
2019-04-09Analyzing Administrative Data with Privacy Protection in Place
2019-04-09Shrinkwrap: Differentially-Private Query Processing in Private Data Federations
2019-04-09Practical Difficulties in the Application of Differential Privacy for the Release of Large-Scale...
2019-04-08The Structure of Optimal Private Tests for Simple Hypotheses
2019-04-08Differentially Private Inference for Binomial Data
2019-04-08Robust Statistics and Bias Correction: Ideas for Differential Privacy and Utility
2019-04-08Differential Privacy with Elliptical Stochastic Processes


Tags:
Simons Institute
Theory of Computing
Theory of Computation
Theoretical Computer Science
Computer Science
UC Berkeley
Privacy and the Science of Data Analysis